The current thesis’s scope is within the Natural Language Understanding sub-field of Natural Language Processing. From the multiple possible tasks from this domain, we stopped at Discourse Analysis. We analyzed the main approaches existent in this field and identified the flaws of each of the presented approaches. Starting from them, we proposed an adaptation of an existing framework (the Polyphonic framework) using ideas derived from the theory of a known linguist (Tannen) regarding the importance of repetitions in discourse. After presenting our adaptation, we showed how it would solve most of the indicated problems with the other approaches. In order to verify the effectiveness of the adapted framework, we presented a couple of developed applications that are meant to demonstrate its utility for discourse visualizations, for the identification and classification of the important moments of a discourse, for the assessment of chat conversations based on repetition and rhythmicity, for malapropism detection and correction, and for text recovery
Extraction of Socio-Semantic Data from Chat Conversations in Collaborative Le...Traian Rebedea
The document summarizes research on extracting socio-semantic data from chat conversations in collaborative learning communities. The goals are to automatically determine relationships between utterances, assess learners' competencies, and visualize the conversation graph. Key techniques include detecting topics, discovering implicit references between utterances, and representing the conversation as a directed acyclic graph to identify important utterances and discussion threads. The work integrates ideas from sociocultural learning theory, natural language processing, and machine learning.
Discourse analysis involves analyzing language in its social context. It analyzes real texts, not artificial ones, and looks at utterances rather than isolated sentences. There are several approaches to discourse analysis, including sociology, ethnography, variation theory, and systemic functional linguistics. Spoken and written discourse differ in aspects like lexical density, grammar use, and repetition of words. Corpus linguistics uses large text databases to quantitatively and qualitatively analyze patterns of language use and variation in discourse. Discourse analysis can inform language pedagogy by helping teachers delineate genres, explain text features, evaluate student performance, and teach discourse structures.
Shallow parsing is a technique that divides text such as sentences into constituent parts and describes the syntactic relationships between those parts, but does not fully analyze internal structure or function. It aims to infer as much structure as possible from morphological and word order information. Typical modules include part-of-speech tagging, chunking of phrases, and relation finding between chunks. Shallow parsers are useful for processing large texts and are more robust to noise than deep parsers.
This document discusses various approaches to discourse analysis, including:
1) Speech act theory which views language as performing actions and analyzes utterances based on illocutionary force.
2) Interactional sociolinguistics which examines how context influences production and interpretation of discourse through cues like intonation.
3) Ethnography of communication which analyzes speech events within their social and cultural contexts using Hymes' SPEAKING framework.
4) Conversation analysis which identifies turn-taking and adjacency pairs as fundamental units and examines how conversation is achieved interactively.
This document provides an introduction to critical applied linguistics. It begins by defining critical applied linguistics as a critical approach to applied linguistics. It then outlines some key concerns of critical applied linguistics, including relating the micro-level of language to the macro-level of society, understanding the relationship between theory and practice, and different understandings of what it means to be "critical." The introduction discusses critical applied linguistics as a constant questioning of assumptions within applied linguistics from a perspective focused on social inequality.
This document provides an overview of discourse analysis including definitions, approaches, and how it relates to other fields. It defines discourse analysis as the study of language use beyond the sentence level, including how language functions in social and cultural contexts. Three main approaches are discussed: speech act theory which examines communicative acts, ethnography of communication which analyzes patterns of communication in cultures, and pragmatics which studies how context informs meaning. The document also explains how discourse analysis relates to other fields like sociolinguistics, psycholinguistics, and pragmatics through their shared interests but different data sources.
1. The document provides an overview of discourse analysis, which is the study of language use in context. It discusses the historical development of the field and various approaches to analyzing both spoken and written discourse.
2. Key aspects covered include speech acts, discourse structures, models for analyzing classroom conversations and casual talk, cohesion in written texts, interpretation of meaning, and patterns in larger text structures.
3. Discourse analysis examines both form and function in language and how language is used for social purposes. It draws from various related fields and has applications for language teaching.
The document discusses textual relations in the Quran from the perspectives of early Muslim scholars and modern linguistic theories of coherence and relevance. It covers Zarkashi's theory of explicit and implicit relations between verses. It also examines relations between verses through techniques like parallelism, subject shifts, and invocations. Inter-surah relations are discussed through the lens of the opening surah Al-Fatiha and connections between the four long surahs. The conclusion reiterates that the Quran exhibits organic unity through various textual relations.
Extraction of Socio-Semantic Data from Chat Conversations in Collaborative Le...Traian Rebedea
The document summarizes research on extracting socio-semantic data from chat conversations in collaborative learning communities. The goals are to automatically determine relationships between utterances, assess learners' competencies, and visualize the conversation graph. Key techniques include detecting topics, discovering implicit references between utterances, and representing the conversation as a directed acyclic graph to identify important utterances and discussion threads. The work integrates ideas from sociocultural learning theory, natural language processing, and machine learning.
Discourse analysis involves analyzing language in its social context. It analyzes real texts, not artificial ones, and looks at utterances rather than isolated sentences. There are several approaches to discourse analysis, including sociology, ethnography, variation theory, and systemic functional linguistics. Spoken and written discourse differ in aspects like lexical density, grammar use, and repetition of words. Corpus linguistics uses large text databases to quantitatively and qualitatively analyze patterns of language use and variation in discourse. Discourse analysis can inform language pedagogy by helping teachers delineate genres, explain text features, evaluate student performance, and teach discourse structures.
Shallow parsing is a technique that divides text such as sentences into constituent parts and describes the syntactic relationships between those parts, but does not fully analyze internal structure or function. It aims to infer as much structure as possible from morphological and word order information. Typical modules include part-of-speech tagging, chunking of phrases, and relation finding between chunks. Shallow parsers are useful for processing large texts and are more robust to noise than deep parsers.
This document discusses various approaches to discourse analysis, including:
1) Speech act theory which views language as performing actions and analyzes utterances based on illocutionary force.
2) Interactional sociolinguistics which examines how context influences production and interpretation of discourse through cues like intonation.
3) Ethnography of communication which analyzes speech events within their social and cultural contexts using Hymes' SPEAKING framework.
4) Conversation analysis which identifies turn-taking and adjacency pairs as fundamental units and examines how conversation is achieved interactively.
This document provides an introduction to critical applied linguistics. It begins by defining critical applied linguistics as a critical approach to applied linguistics. It then outlines some key concerns of critical applied linguistics, including relating the micro-level of language to the macro-level of society, understanding the relationship between theory and practice, and different understandings of what it means to be "critical." The introduction discusses critical applied linguistics as a constant questioning of assumptions within applied linguistics from a perspective focused on social inequality.
This document provides an overview of discourse analysis including definitions, approaches, and how it relates to other fields. It defines discourse analysis as the study of language use beyond the sentence level, including how language functions in social and cultural contexts. Three main approaches are discussed: speech act theory which examines communicative acts, ethnography of communication which analyzes patterns of communication in cultures, and pragmatics which studies how context informs meaning. The document also explains how discourse analysis relates to other fields like sociolinguistics, psycholinguistics, and pragmatics through their shared interests but different data sources.
1. The document provides an overview of discourse analysis, which is the study of language use in context. It discusses the historical development of the field and various approaches to analyzing both spoken and written discourse.
2. Key aspects covered include speech acts, discourse structures, models for analyzing classroom conversations and casual talk, cohesion in written texts, interpretation of meaning, and patterns in larger text structures.
3. Discourse analysis examines both form and function in language and how language is used for social purposes. It draws from various related fields and has applications for language teaching.
The document discusses textual relations in the Quran from the perspectives of early Muslim scholars and modern linguistic theories of coherence and relevance. It covers Zarkashi's theory of explicit and implicit relations between verses. It also examines relations between verses through techniques like parallelism, subject shifts, and invocations. Inter-surah relations are discussed through the lens of the opening surah Al-Fatiha and connections between the four long surahs. The conclusion reiterates that the Quran exhibits organic unity through various textual relations.
Factors Responsible for Poor English Reading Comprehension at Secondary LevelBahram Kazemian
The present study shows factors responsible for poor English reading comprehension at secondary school level students. The purpose of this study is to explore those factors and to suggest remedies how to strengthen English reading comprehension of the students. English is the 2nd language of Pakistani students and Kachru (1996) places it in the outer circle. Test and interviews are conducted to get the data. Different factors like poor command of vocabulary, habit of cramming, no interest to learn creativity in reading but the sole goal is just to pass the examination which are found responsible for poor English reading comprehension. Motivation to learn reading can develop reading comprehension skill of students.
The outlined approach allows a common philosophical viewpoint to the physical world, language and some mathematical structures therefore calling for the universe to be understood as a joint physical, linguistic and mathematical universum, in which physical motion and metaphor are one and the same rather than only similar in a sense.
The document discusses several theories of second language acquisition (SLA) including behaviorism, acculturation, universal grammar hypothesis, comprehension hypothesis, interaction hypothesis, output hypothesis, sociocultural theory, and connectionism. It argues that previous SLA theories should not be disregarded but viewed as explanations of parts of the whole acquisition process. Finally, it claims that SLA should be seen as a chaotic/complex system based on principles of emergence and complexity theory.
This document discusses discourse analysis and vocabulary. It summarizes Halliday and Hasan's description of lexical cohesion, which refers to related vocabulary items occurring across clause and sentence boundaries to create coherence. There are two principal kinds of lexical cohesion: reiteration, which restates an item through repetition, synonymy or hyponymy; and collocation, the probability that lexical items will co-occur. The document also discusses how speakers reiterate vocabulary in conversation through relexicalisation and how vocabulary helps organize texts into predictable patterns.
Metadiscourse refers to discourse about discourse that helps guide a discussion. It includes words and phrases used to discuss the structure and purpose of a text, as well as comments on ideas and the reader's understanding. Metadiscourse serves as formative evaluation that helps assess progress and plan future directions for knowledge building communities. It reveals the writer's awareness of the reader's needs and can help students advance ideas, set goals, and connect knowledge.
The document discusses discourse analysis and related linguistic concepts. It defines discourse as language above the sentence level, including stretches of spoken language that are coherent and meaningful. It describes two approaches to analyzing discourse: structural, which looks at grammatical relationships between units, and functional, which examines how language performs different social functions. Recent approaches view discourse as a social practice shaped by and having implications for social structures. The document also discusses speech act theory, which proposes that utterances in dialogue perform actions, such as asking a question or making a promise.
This document discusses discourse analysis and vocabulary. It explains that discourse-organizing words help signal larger textual patterns and parcel up phrases and sentences. Examples of discourse patterns include problem-solution, claim-counterclaim, and doubt/uncertainty. Register and idioms also help organize discourse. Modality expresses certainty, possibility, volition, permission and obligation and conveys stance. Studying vocabulary in discourse looks at patterns across clauses/sentences and how certain words organize structure and register. Collecting vocabulary along discourse-functional lines can motivate word lists beyond traditional semantic fields.
The document describes a computational model of psycholinguistics called INSOMNet that incrementally constructs explicit semantic representations as natural language is processed. The model scales up to large corpora while demonstrating on-line behaviors observed in human sentence comprehension like anticipating upcoming words based on linguistic and visual context cues. Simulations show the model can accurately interpret sentences when provided a matching visual scene and begin disambiguating ambiguities early.
Conversation analysis is a research tradition that examines recorded, naturally occurring conversations to understand how participants organize turn-taking and negotiate relationships. It believes interaction determines social dynamics. Researchers analyze transcripts of audio/video recordings without hypotheses, focusing on patterns across contexts. The goal is describing competencies that enable intelligible social interaction. Reports provide context, describe phenomena through examples from data, and interpret underlying organizational patterns.
This document discusses discourse analysis and its relationship to culture and pragmatics. It defines pragmatics as the study of contextual meaning and discourse as spoken or written language use within a context. Discourse analysis investigates the form and function of language and how it relates to society. Culture is depicted through language and influences pragmatics through cultural schemata and cross-cultural differences in interactive strategies between languages. Discourse analysis focuses on how language is used in context and what speakers intend through assumptions of coherence and background knowledge.
Bell proposes including translation theory within applied linguistics, specifically within human communication. He considers a translator to be a communicator who processes both information and texts, requiring procedural and factual knowledge. According to Bell, a translator should possess communicative competence, including grammatical, sociolinguistic, discourse, and strategic abilities. A translator also needs linguistic competence in both the source and target languages as well as communicative competence in both cultures. Bell outlines steps for translation involving analysis of syntax, semantics, and pragmatics, followed by synthesis of pragmatics, semantics, and syntax.
This document outlines areas of research in translation studies, including text analysis and translation quality assessment, genre translation, multimedia translation, translation history, and the translation process. It discusses both conceptual and empirical research. Empirical research uses methodology like quantitative and qualitative methods, case studies, corpus studies, text analysis, and interviews. Research questions can be exploratory to understand what is happening, or descriptive to analyze translations and understand patterns. Hypotheses are used if researchers want to generalize findings.
Discourse analysis is the study of the relationship between language and context. It examines both the form and function of language. Form refers to structure and appearance, while function looks at how language is used to make sentences grammatically correct through tools like pronouns, determiners, conjunctions, prepositions, and auxiliary verbs. Speech act theory considers what language is doing and how listeners are supposed to react. Discourse analysts are interested in both spoken and written interactions, and how teaching materials and classroom language are structured. Models of spoken discourse analysis examine conversation patterns both in and out of classroom settings. Written discourse allows more time for composition compared to spontaneous speech.
Pragmatics is the study of how context contributes to meaning in language. It includes speech act theory, conversational implicature, and other approaches to understanding language use. Pragmatics examines how the actual meaning of an utterance is understood based on the context, including who is speaking, their shared knowledge and assumptions, and conversational implicatures which are meanings implied but not directly stated. Conversation analysis is one approach used in pragmatics to study how participants construct turns in conversation and repair problems. Discourse refers to a instance of language that can be classified based on factors like grammar, lexicon, themes, and the knowledge framework of the listener. An implicature is any inferred meaning from an utterance that is not essential to
The document summarizes Roger Bell's work on translation theory and the abilities of a translator. It discusses Bell's view that a translator is a communicator who processes information and texts. Bell proposes including translation theory in applied linguistics as part of human communication. According to Bell, a translator must have communicative competence including grammatical, sociolinguistic, discourse, and strategic competence. A translator also needs linguistic competence in both the source and target languages as well as communicative competence in both cultures. The document outlines Bell's model of the cognitive process of translation and the steps of analysis, synthesis, and processing texts.
The document discusses the role of a translator as a mediator between two cultures. It explains that a translator must have in-depth knowledge of both the source and target cultures in order to adequately translate texts while accounting for cultural codes and differences. Specifically, the document states that without knowledge of cultural codes, it is better not to translate at all. It also outlines four key abilities - abstraction, decision, transfer, and criticism - that translators must develop to translate effectively.
Crafting astrological advertisements in pakistan; a systemic functional analysisAzam Almubarki
The document analyzes three astrological advertisements from Pakistani newspapers using Systemic Functional Linguistics. It examines how the advertisers use language to persuade readers by invoking superstitious beliefs and claiming to have solutions for problems. The analysis explores the three metafunctions of meaning - textual, interpersonal, and ideational. Key aspects analyzed include themes, modality, and language choices that enact social roles between the advertisers and readers.
The document describes a tool for discourse analysis and visualization that was developed to analyze different types of discourses. The tool combines cognitive and socio-cultural paradigms using the concept of voice from polyphony theory. It identifies important voices in a text through lexical chains and displays the discourse through different views including word-level representations that show voice frequency and distribution, sentence-level representations that show voice distribution across sentences, and identification of pivotal moments where voices intersect. The tool was evaluated on collaborative learning chats and showed potential to accurately assess discussion quality and compare different discourses.
Lecture 1st-Introduction to Discourse Analysis._023928.pptxGoogle
Introduction to discourse analysis
What is discourse?
What is discourse Analysis?
Paradigms in linguistics
Cohesion and Coherense
Types of written discourse
Types of spoken discourse
Text and discourse
Scope of discourse analysis
Factors Responsible for Poor English Reading Comprehension at Secondary LevelBahram Kazemian
The present study shows factors responsible for poor English reading comprehension at secondary school level students. The purpose of this study is to explore those factors and to suggest remedies how to strengthen English reading comprehension of the students. English is the 2nd language of Pakistani students and Kachru (1996) places it in the outer circle. Test and interviews are conducted to get the data. Different factors like poor command of vocabulary, habit of cramming, no interest to learn creativity in reading but the sole goal is just to pass the examination which are found responsible for poor English reading comprehension. Motivation to learn reading can develop reading comprehension skill of students.
The outlined approach allows a common philosophical viewpoint to the physical world, language and some mathematical structures therefore calling for the universe to be understood as a joint physical, linguistic and mathematical universum, in which physical motion and metaphor are one and the same rather than only similar in a sense.
The document discusses several theories of second language acquisition (SLA) including behaviorism, acculturation, universal grammar hypothesis, comprehension hypothesis, interaction hypothesis, output hypothesis, sociocultural theory, and connectionism. It argues that previous SLA theories should not be disregarded but viewed as explanations of parts of the whole acquisition process. Finally, it claims that SLA should be seen as a chaotic/complex system based on principles of emergence and complexity theory.
This document discusses discourse analysis and vocabulary. It summarizes Halliday and Hasan's description of lexical cohesion, which refers to related vocabulary items occurring across clause and sentence boundaries to create coherence. There are two principal kinds of lexical cohesion: reiteration, which restates an item through repetition, synonymy or hyponymy; and collocation, the probability that lexical items will co-occur. The document also discusses how speakers reiterate vocabulary in conversation through relexicalisation and how vocabulary helps organize texts into predictable patterns.
Metadiscourse refers to discourse about discourse that helps guide a discussion. It includes words and phrases used to discuss the structure and purpose of a text, as well as comments on ideas and the reader's understanding. Metadiscourse serves as formative evaluation that helps assess progress and plan future directions for knowledge building communities. It reveals the writer's awareness of the reader's needs and can help students advance ideas, set goals, and connect knowledge.
The document discusses discourse analysis and related linguistic concepts. It defines discourse as language above the sentence level, including stretches of spoken language that are coherent and meaningful. It describes two approaches to analyzing discourse: structural, which looks at grammatical relationships between units, and functional, which examines how language performs different social functions. Recent approaches view discourse as a social practice shaped by and having implications for social structures. The document also discusses speech act theory, which proposes that utterances in dialogue perform actions, such as asking a question or making a promise.
This document discusses discourse analysis and vocabulary. It explains that discourse-organizing words help signal larger textual patterns and parcel up phrases and sentences. Examples of discourse patterns include problem-solution, claim-counterclaim, and doubt/uncertainty. Register and idioms also help organize discourse. Modality expresses certainty, possibility, volition, permission and obligation and conveys stance. Studying vocabulary in discourse looks at patterns across clauses/sentences and how certain words organize structure and register. Collecting vocabulary along discourse-functional lines can motivate word lists beyond traditional semantic fields.
The document describes a computational model of psycholinguistics called INSOMNet that incrementally constructs explicit semantic representations as natural language is processed. The model scales up to large corpora while demonstrating on-line behaviors observed in human sentence comprehension like anticipating upcoming words based on linguistic and visual context cues. Simulations show the model can accurately interpret sentences when provided a matching visual scene and begin disambiguating ambiguities early.
Conversation analysis is a research tradition that examines recorded, naturally occurring conversations to understand how participants organize turn-taking and negotiate relationships. It believes interaction determines social dynamics. Researchers analyze transcripts of audio/video recordings without hypotheses, focusing on patterns across contexts. The goal is describing competencies that enable intelligible social interaction. Reports provide context, describe phenomena through examples from data, and interpret underlying organizational patterns.
This document discusses discourse analysis and its relationship to culture and pragmatics. It defines pragmatics as the study of contextual meaning and discourse as spoken or written language use within a context. Discourse analysis investigates the form and function of language and how it relates to society. Culture is depicted through language and influences pragmatics through cultural schemata and cross-cultural differences in interactive strategies between languages. Discourse analysis focuses on how language is used in context and what speakers intend through assumptions of coherence and background knowledge.
Bell proposes including translation theory within applied linguistics, specifically within human communication. He considers a translator to be a communicator who processes both information and texts, requiring procedural and factual knowledge. According to Bell, a translator should possess communicative competence, including grammatical, sociolinguistic, discourse, and strategic abilities. A translator also needs linguistic competence in both the source and target languages as well as communicative competence in both cultures. Bell outlines steps for translation involving analysis of syntax, semantics, and pragmatics, followed by synthesis of pragmatics, semantics, and syntax.
This document outlines areas of research in translation studies, including text analysis and translation quality assessment, genre translation, multimedia translation, translation history, and the translation process. It discusses both conceptual and empirical research. Empirical research uses methodology like quantitative and qualitative methods, case studies, corpus studies, text analysis, and interviews. Research questions can be exploratory to understand what is happening, or descriptive to analyze translations and understand patterns. Hypotheses are used if researchers want to generalize findings.
Discourse analysis is the study of the relationship between language and context. It examines both the form and function of language. Form refers to structure and appearance, while function looks at how language is used to make sentences grammatically correct through tools like pronouns, determiners, conjunctions, prepositions, and auxiliary verbs. Speech act theory considers what language is doing and how listeners are supposed to react. Discourse analysts are interested in both spoken and written interactions, and how teaching materials and classroom language are structured. Models of spoken discourse analysis examine conversation patterns both in and out of classroom settings. Written discourse allows more time for composition compared to spontaneous speech.
Pragmatics is the study of how context contributes to meaning in language. It includes speech act theory, conversational implicature, and other approaches to understanding language use. Pragmatics examines how the actual meaning of an utterance is understood based on the context, including who is speaking, their shared knowledge and assumptions, and conversational implicatures which are meanings implied but not directly stated. Conversation analysis is one approach used in pragmatics to study how participants construct turns in conversation and repair problems. Discourse refers to a instance of language that can be classified based on factors like grammar, lexicon, themes, and the knowledge framework of the listener. An implicature is any inferred meaning from an utterance that is not essential to
The document summarizes Roger Bell's work on translation theory and the abilities of a translator. It discusses Bell's view that a translator is a communicator who processes information and texts. Bell proposes including translation theory in applied linguistics as part of human communication. According to Bell, a translator must have communicative competence including grammatical, sociolinguistic, discourse, and strategic competence. A translator also needs linguistic competence in both the source and target languages as well as communicative competence in both cultures. The document outlines Bell's model of the cognitive process of translation and the steps of analysis, synthesis, and processing texts.
The document discusses the role of a translator as a mediator between two cultures. It explains that a translator must have in-depth knowledge of both the source and target cultures in order to adequately translate texts while accounting for cultural codes and differences. Specifically, the document states that without knowledge of cultural codes, it is better not to translate at all. It also outlines four key abilities - abstraction, decision, transfer, and criticism - that translators must develop to translate effectively.
Crafting astrological advertisements in pakistan; a systemic functional analysisAzam Almubarki
The document analyzes three astrological advertisements from Pakistani newspapers using Systemic Functional Linguistics. It examines how the advertisers use language to persuade readers by invoking superstitious beliefs and claiming to have solutions for problems. The analysis explores the three metafunctions of meaning - textual, interpersonal, and ideational. Key aspects analyzed include themes, modality, and language choices that enact social roles between the advertisers and readers.
The document describes a tool for discourse analysis and visualization that was developed to analyze different types of discourses. The tool combines cognitive and socio-cultural paradigms using the concept of voice from polyphony theory. It identifies important voices in a text through lexical chains and displays the discourse through different views including word-level representations that show voice frequency and distribution, sentence-level representations that show voice distribution across sentences, and identification of pivotal moments where voices intersect. The tool was evaluated on collaborative learning chats and showed potential to accurately assess discussion quality and compare different discourses.
Lecture 1st-Introduction to Discourse Analysis._023928.pptxGoogle
Introduction to discourse analysis
What is discourse?
What is discourse Analysis?
Paradigms in linguistics
Cohesion and Coherense
Types of written discourse
Types of spoken discourse
Text and discourse
Scope of discourse analysis
Models of Parsing: Two-Stage Models
Models of Parsing: Constraint-Based Models
Story context effects
Subcategory frequency effects
Cross-linguistic frequency data
Semantic effects
Prosody
Visual context effects
Interim Summary
Argument Structure Hypothesis
Limitations, Criticisms, and Some Alternative Parsing Theories
Construal
Race-based parsing
Good-enough parsing
Parsing Long-Distance
Dependencies
Summary and Conclusions
Test Yourself
When people speak, they produce sequences of words. When people listen or read, they also deal with sequences of words. Speakers systematically organize those sequences of words into phrases, clauses, and sentences.
The study of syntax involves discovering the cues that languages provide that show how words in sentences relate to one another.
The study of syntactic parsing involves discovering how comprehenders use those cues to determine how words in sentences relate to one another during the process of interpreting sentence.
Parsing means to breaking down a sentence into its component parts so that the meaning of the sentence can be understood.
This can either be the category of words (Nouns, Pronouns, verbs, adjectives. Etc.)
Or other elements such as verbs tense (present, past, future)
In a phrase structure tree, the labels, like NP, VP, and S, are called nodes and the connections between the different nodes form branches.
The patterns of nodes and branches show how the words in the sentence are grouped together to form phrases and clauses.
We all do our research and put an effort in making a clear and an accurate presentation, but I'd be glad if this could help especially for those who are taking major in English and the like. Good luck!
A proper credit would be appreciated.
• Jay-ar A. Padernal, BSEd Major in English, University of Mindanao
Discourse analysis examines language use beyond the sentence level and how language is used in social contexts, while text analysis focuses on formal linguistic cohesive devices within written texts. Some researchers use the terms interchangeably, but most agree the distinction is unclear. Discourse analysis is broader in investigating language in use with consideration of context, while text analysis concentrates on linguistic features linking sentences. The field would benefit from abandoning the term "text" in favor of discourse analysis to avoid confusion.
The document presents a holistic model of language that incorporates four main theories: formal, functional, systemic, and relativistic models. It argues that considering language from only one of these angles provides an incomplete picture. The proposed holistic model incorporates insights from all four theories and suggests that excluding any single theory would render the model incomplete. The document reviews the key aspects and components of each theory and proposes that taking a multi-angled perspective that includes formalism, functionalism, systemic approaches, and relativism can lead to a more integrated understanding of language.
Discourse analysis considers language use beyond the sentence level and in its full social context. It examines how texts are structured through cohesion and coherence. Cohesion refers to linguistic connections between parts of a text, while coherence is the meaningful unity created in the reader's mind. Discourse analysis also looks at spoken and written styles, genres, and conversation structure through phenomena like turn-taking, adjacency pairs, and back-channeling. Background knowledge and expectations also influence how a text is understood.
The document discusses key concepts and definitions in discourse analysis including:
- Reality is constructed through language and discourse shapes how we understand the world.
- Discourse analysis examines patterns in language use and how these patterns maintain and transform understandings of social realities.
- A discourse analyst's toolkit includes analyzing deixis, fillers, reframing language to identify taken-for-granted assumptions, and cognitive linguistics concepts like figure-ground asymmetries.
Discourse Analysis Weeks 1,2,3 and 4.pdfAmadStrongman
This document provides an introduction to the course "Introduction to Discourse Analysis" taught by Abdelmalek El Kadoussi. It discusses key topics that will be covered in the course including defining discourse and discourse analysis, examining language use in context, relationships between discourse and knowledge/society/genres/conversation, and approaches like critical discourse analysis. The course outline lists the weekly topics to be covered over 12 weeks. It emphasizes that discourse analysis considers how language varies based on factors like subject area, social context, culture, and participant identities.
A Text Analysis Of A Newspaper Article About Konglish Taken From The Korea H...Lori Moore
The document analyzes a newspaper article about Konglish (Korean-influenced English) from The Korea Herald. It follows an overall general-specific pattern. This is signaled by words like "recently" and "increasing amount of attention" in the introduction, establishing a general context. The body then provides more specific details about the study of written discourse and textual patterns. It concludes with another general statement about the implications for language teaching. Within this overall pattern, subordinate patterns include problem-solution, as signaled by words such as "problem" and "solution" when discussing analyzing textual patterns.
This document discusses the difference between form and function in discourse analysis. Form refers to syntactic structure like words and sentences, while function refers to the purpose words and structures serve. While form and structure can predict function, context is also important, as the same form can take on different functions. Two approaches to discourse analysis are described: structural, which looks at linguistic units and their relationships, and functional, which analyzes language use and Jakobson's six functions of language.
The document summarizes Norman Fairclough's dialectical-relational approach to critical discourse analysis (CDA). It outlines Fairclough's three-dimensional framework for analyzing discourse as text, discursive practice, and social practice. For each dimension, Fairclough proposes specific analytical categories and concepts, including textual analysis of vocabulary, grammar, cohesion and structure; discursive analysis of utterance force, text coherence and intertextuality; and social analysis of the relationship between discourse and power/ideology. The document provides an overview of Fairclough's influential work developing CDA and his dialectical theory of discourse.
Semiotics and conceptual modeling gv 2015Guido Vetere
- Conceptual modeling in computer science often uses concepts that require interpretation, such as linguistic concepts, which challenges the model-theoretic semantics approach of formal logic.
- Semiotics, as the study of signs and their interpretation, can provide a theoretical foundation for more formally and transparently addressing interpretation in conceptual models.
- Ongoing research explores applying semiotic perspectives to linking ontologies and lexical resources to systematically represent the relationships between concepts, senses, and interpretations.
This document discusses sentence comprehension and some of the key theories about how it works. It defines sentence comprehension as understanding the meaning derived from words based on linguistic structures and constraints. Some important factors in comprehension are grammatical roles, sentence structure, and identifying constituents. Sentence comprehension must deal with ambiguities. Theories discuss modular vs. interactive processing, serial vs. parallel construction of interpretations, and models like the Garden Path model and constraint-based models that integrate probabilistic information.
This document discusses different perspectives on analyzing discourse. It argues that discourse is best analyzed as a process rather than a structured entity. It proposes that procedural pragmatics, which aims to operationalize cognitive pragmatics, can provide a model for tracking the step-by-step processes of contextualization that underlie discourse interpretation. Discourse can be viewed as the dynamic modification of representations through successive utterances, rather than as a singular object with its own structural properties.
This document discusses different perspectives on analyzing discourse. It argues that discourse is best analyzed as a process rather than a structured entity. It proposes that procedural pragmatics, which aims to operationalize cognitive pragmatics, can provide a model for tracking the step-by-step processes of contextualization that underlie discourse interpretation. Discourse can be viewed as the dynamic modification of representations through successive utterances, rather than as a singular object in itself.
Systemic Functional Linguistics: An approach to analyzing written academic di...ClmentNdoricimpa
Written academic discourse refers to the way of thinking and using language that exist in the academy. Writers demonstrate knowledge and negotiate social relations with readers by means of written discourse. In order to understand these characteristics of written discourse, different approaches are followed. Some follow a linguistic approach to uncover the linguistic devices associated with coherence in a written text. Other follow a social approach to analyze the social cultural context in which a written text occurs. However, it is demonstrated that the linguistic and the social cultural elements in a written text cannot be disassociated and that an approach, which combine the two approaches is required. Such an approach is Systemic Functional Linguistics (SFL). Therefore, this paper discusses the way in which SFL is used as an approach to analyzing linguistic features of academic discourses and how those features relate to social cultural context. In this paper, it is shown that SFL provides the means to analyze not only the linguistic resources employed in a written text but also the context in which the text is used. These linguistic resources are associated with the creation of ideational, interpersonal and textual meaning at the level of lexicogrammar and discourse semantic. The context is modelled through register and genre theory.
- The document describes using time series analysis models like ARIMA to forecast daily sales quantities of products like paintings for an online retailer.
- The best model was found to be an ARIMA(7,0,2) model, which uses the previous 7 days' values to predict future values without differencing the data.
- This model provided more accurate predictions than the Facebook Prophet model based on error metrics, while converging during both training and testing.
The document describes improvements made to an existing application used to identify important moments in student collaborative chats. The improvements include: 1) Implementing a redirection system to analyze utterance timestamps to identify intense discussion periods, 2) Overlapping graphics to correlate concepts with disputed chat parts to identify more important concepts, 3) Increasing availability by creating a web application and avoiding user intervention for moment detection. The improved application can better identify important moments by considering both concept distribution and dialogue intensity over time.
The document summarizes a research paper on developing digital services to emphasize pollution phenomena using statistics and time series analysis. The paper presented at the 8th International Conference on Exploring Services Science discusses how it extracts concepts related to pollution from literature, analyzes frequency of concepts over time, and identifies peaks that correspond to pollution events. It finds that awareness of pollution threats increased in the late 1960s and presents limitations such as delays in reporting events and difficulty identifying all factors influencing time series. The methodology could be improved by better distinguishing yearly events and developing predictive models.
These slides present an application for identifying English words whose use is cyclic or regularly varies in time. The purpose of the developed application was to build a cross-platform system for indexing and analyzing the graphs of words usage over time. For words indexing, we used the data provided by the Google Books N-grams Corpus, which was afterwards filtered using the WordNet lexical database. For identifying the cyclic or regularly varying words, we used two different algorithms: autocorrelation and dynamic time warping. The results of the analysis can be visualized using a web interface. The application also offers the possibility to view the evolution of the use frequency of different words in time.
These slides present an application designed to analyze news articles from Romanian mass media and extract opinions about political entities relevant to the major political stage. The application was created with the desire to study media polarization around important political events, such as legislative or presidential elections. The application uses different crawlers to extract the data from online newspapers and save it in the database. Then, it uses several Machine Learning techniques for identifying and classifying opinions about given entities over a long span of time. Based on this classification, it generates reports and charts that could be use not only to study political polarization, but also to identify partisan media
Language is a living corpus, words tending to be created, or to disappear over time. Even the degree of certain words' usage tends to fluctuate due to historical events, cultural movements or scientific discoveries. The changes from the lan-guage are reflected in the written texts and thus, by tracking them one can deter-mine the moment when these texts were written. In this paper, we present an ap-plication that uses time series analysis built on top of the Google Books N-gram corpus to determine the time period during which a text was written. The applica-tion is based on words' fingerprinting to find the time interval when they were most probable used and on word' importance for the given text. Combining the fingerprints for all the text's words according to their importance allows the time stamping of that text.
These slides address the issue of predicting the reselling price of cars based on ads extracted from popular websites for reselling cars. To obtain the most accurate predictions, we have used two machine learning algorithms (multiple linear regression and random forest) to build multiple models to reflect the importance of different combinations of features in the final price of the cars. The predictions are generated based on the models trained on the ads extracted from such sites. The developed system provides the user with an interface that allows navigation through ads to assess the fairness of prices compared to the predicted ones
These slides address the problem of capturing, processing and analyzing images from the video stream of the Hearthstone game in order to obtain relevant information on the conduct of parties in this game. Since the information needs to be presented to the user in real-time, we needed to find the most suitable methods of extracting this information. Therefore, techniques such as background subtraction, histograms comparisons, key points matching, optical character recognition were investigated. Driven by the required processing speed, we ended up using optical character recognition on limited areas of interest from the captured image. After developing the application, we tested it in real-world context, while real games were played and presented the obtained results. In the end, we also provided two examples where the application would prove useful for better decision making during the game.
These slides present Movie Recommender, a system which provides movie recommendations based on the information known about the users. These recommendations are done using the analysis of the users' psychological profile, their watching history and the movies scores from other websites. They are based on aggregate similarity calculation. The system uses both collaborative filtering and content filtering (using an approach based on different features of the movies from the database). Although there are similar applications available, they tend to ignore the data specific to the user, which in our opinion is essential for his/her behavior
Language suffers an everlasting process of change, both at a semantic level, where existing words acquire new meanings, and at a lexical level, where new concepts appear and old ones disappear or are used less frequently. New words (terms/concepts) may be added as a result of scientific discoveries or socio-cultural influences, while other words are ”forgotten” or are assigned alternative meanings. These changes in a vocabulary usually characterize important shifts in the environment or
the domain they are used in. For experts there is an evident connection between a new concept and some of the existing ones, but for regular people these relations remain hidden and need to be identified. In particular, in the medical domain new terms appear as a result of new discoveries and it becomes an important challenge to establish the connections between different concepts. Moreover, it is important to detect if such a relation even exists. In this paper, we present a graph-based approach to identify the semantic path (which is a chain of semantically related words) between the concepts that appeared in the bio-medicine publications available in the PubMed corpus over a time period of 20 years
Public data can be considered large and important sources of data that can be used for different purposes. In this paper we present a method for collecting and analyzing data within urban settlements. For more focused analysis and gathering of large amount of data we considered a case study of Bucharest. The main purpose of this analysis is to pick up important information about different streets, points of interests, details about urban planning, etc., with the goal of facilitating a quick and correct evaluation of specific areas and identifying suitable location for adding new points of interest. The prediction of suitable location involves using heuristics and data mining technics such as clustering algorithms, association rules
These slides present an application for identifying archaisms and neologisms in texts. The application also provides the ability to view graphically the evolution trends of these words for a better interpretation of the results. The presented solution consists of two phases: the learning phase in which we identify the general evolution trends of three categories of words (archaisms, neologisms and common words) and the classification phase in which we label new words with their corresponding category. For both phases, the application requires Internet access because it is using the Google Books N-gram Viewer to generate the images that back up the decisions
These slides present an automatic system used for the evaluation of Bachelor and Master thesis of Computer Science students. In order to be able to fulfill this task, we have used text complexity measures along with other factors to evaluate the students' thesis. Text complexity has been mainly used to predict the grade level for which a specific reading passage or text should be assigned to. Also, it has been used in evaluating students' writings in language classes. We have decided to try to use text complexity measures for evaluating students' graduation thesis. The main challenges of this task are to select the best features that accurately reflect student's performance in a specific domain, and to identify the optimal classifier to predict the student's score. Firstly, we investigated four sets of text complexity measures (lexical, syntactic, semantic, and character measures), cohesion metrics and a couple of features related to the thesis organization and to the references and bibliography. Secondly, we computed the correlation between the proposed features and we excluded the highly inter-correlated ones. After that, we used several classifiers to predict the students' grade levels and to compare their performances. Finally, we tested our work on a corpus of Bachelor and Master thesis from the students of the Computer Science Department of the University Politehnica of Bucharest that were written in English (as for English there is a high availability of open-source tools for natural language processing). We evaluated the quality of the presented application using Pearson's Rank Correlation to compare our results with the students' grades assigned by the evaluation committee for their thesis
Every country has its own topics of interest and its hot topics at different moments in time. In this paper we present a system that helps to understand and compare different countries, starting from the topics that are debated between their members. In order to do that, we recorded and analyzed the content of the messages that are sent on Twitter by people living in several countries, hoping that this way we will be able to capture the topics of interest for each culture and predict their hot topics. We did our analysis on English written tweets only, based on the fact that English has become a global language, being spoken even by Internet users from non-English speaking countries when they want to share their thoughts and have a global audience for their messages. Our study is trying to capture the topic models both for the tweets and for the URLs shared in them. Then we compare the distribution of topics across different countries both for the tweets and for the URLs to check how consistent these models are. For the topic modelling task, we designed a specialized way of developing them that is adapted for tweets (which have a maximum of 140 characters, being too short to apply classical topic modelling methods). Our system has been tested on a corpus consisting on English tweets, collected using the Twitter streaming API, that have a location attached to them and that also contain an URL. In order to eliminate our bias, we extracted tweets without any restrictions (including tweets written in other languages, tweets without URLs, tweets without location attached) and then we checked the percentage of our targeted tweets for each country. As a consequence, we extended the period of collecting the tweets to decrease the risk of dealing with abnormal events occurring in a certain country
These slides present a text segmentation system based on the sentiments expressed in the text. The system takes as input plain text (product review for instance) and uses two different resources for tagging the sentiment words: a sentiment words dictionary and SentiWordNet. Once the sentiment words are identified, the initial text is annotated with segmentation markers when polarity shifts. The system also outputs the counts of positive and negative sentiment words found in text and optionally annotates them with their valence
In these slides we present a model that was intended to discriminate creative from non-creative news articles. In order to build the classifier, we have combined nine different measures using a stepwise logistic regression model. The obtained model was tested in two experiments: the first one tried to discriminate between news articles about the US 2012 Elections from different newspapers versus articles taken from The Onion (a website providing satiric news) on the same subject, while the second one evaluated the capacity of the model to generalize over different topics and text genres. The experiments showed that the system achieves 80% accuracy, but the lack of true positives from the second experiment raised the question of whether we really identified creativity or in fact we detected satire (as the assumption for the training corpus was that the satiric news from The Onion were also creative).
The document presents a methodology for automatically assessing participants in chat conversations used for computer-supported collaborative learning (CSCL). It uses natural language processing techniques and heuristics to evaluate conversations based on participants' involvement, knowledge, and innovation. The heuristics were tested on a corpus of 7 chat conversations involving 35 students discussing web collaboration technologies. Correlations between the heuristic evaluations and expert human evaluations were generally high, particularly for involvement and innovation. The knowledge heuristic was less reliable. The methodology can help identify effective participation criteria and rank learners and conversations.
In this poster paper we propose a new method for identifying creativity that is based on analyzing a corpus of chat conversations on the same topic and extracting the new ideas expressed by participants. The application is a first step in supporting creativity in online group discussions by highlighting the novel concepts present in conversations (new ideas) and also by identifying topics that could have become important, if not forgotten during the debates (lost ideas)
Because of the ubiquity of metaphors in language, metaphor processing is a very important task in the field of natural language processing. The first step towards metaphor processing, and probably the most difficult one, is metaphor detection. In the first part of this paper, we review the theoretical background for metaphors and the models and implementations that have been proposed for their detection. We then build corpora for detecting three types of metaphors: IS-A metaphors, metaphors formed with the preposition ‘of’ and metaphors formed with a verb. For the first two tasks, we train supervised classifiers using semantic features. For the third task, we use features commonly used in text categorization
The main objective of this paper is to compare
the sentiments that prevailed before and after the presidential
elections, held in both US and France in the year 2012. To
achieve this objective we extracted the content information from a
social medium such as Twitter and used the tweets from electoral
candidates and the public users (voters), collected by means of
crawling during the course of election. In order to gain useful
insights about the US elections, we scored the sentiments for
each tweet using different metrics and performed a time series
analysis for candidates and different topics (identified by specific
keywords). In addition to this, we compared some of our insights
obtained from the US election with what we have observed for
the French election. This deep dive analysis was done in order
to understand the inherent nature of elections and to bring out
the influence of social media on elections.
Fueling AI with Great Data with Airbyte WebinarZilliz
This talk will focus on how to collect data from a variety of sources, leveraging this data for RAG and other GenAI use cases, and finally charting your course to productionalization.
Infrastructure Challenges in Scaling RAG with Custom AI modelsZilliz
Building Retrieval-Augmented Generation (RAG) systems with open-source and custom AI models is a complex task. This talk explores the challenges in productionizing RAG systems, including retrieval performance, response synthesis, and evaluation. We’ll discuss how to leverage open-source models like text embeddings, language models, and custom fine-tuned models to enhance RAG performance. Additionally, we’ll cover how BentoML can help orchestrate and scale these AI components efficiently, ensuring seamless deployment and management of RAG systems in the cloud.
Driving Business Innovation: Latest Generative AI Advancements & Success StorySafe Software
Are you ready to revolutionize how you handle data? Join us for a webinar where we’ll bring you up to speed with the latest advancements in Generative AI technology and discover how leveraging FME with tools from giants like Google Gemini, Amazon, and Microsoft OpenAI can supercharge your workflow efficiency.
During the hour, we’ll take you through:
Guest Speaker Segment with Hannah Barrington: Dive into the world of dynamic real estate marketing with Hannah, the Marketing Manager at Workspace Group. Hear firsthand how their team generates engaging descriptions for thousands of office units by integrating diverse data sources—from PDF floorplans to web pages—using FME transformers, like OpenAIVisionConnector and AnthropicVisionConnector. This use case will show you how GenAI can streamline content creation for marketing across the board.
Ollama Use Case: Learn how Scenario Specialist Dmitri Bagh has utilized Ollama within FME to input data, create custom models, and enhance security protocols. This segment will include demos to illustrate the full capabilities of FME in AI-driven processes.
Custom AI Models: Discover how to leverage FME to build personalized AI models using your data. Whether it’s populating a model with local data for added security or integrating public AI tools, find out how FME facilitates a versatile and secure approach to AI.
We’ll wrap up with a live Q&A session where you can engage with our experts on your specific use cases, and learn more about optimizing your data workflows with AI.
This webinar is ideal for professionals seeking to harness the power of AI within their data management systems while ensuring high levels of customization and security. Whether you're a novice or an expert, gain actionable insights and strategies to elevate your data processes. Join us to see how FME and AI can revolutionize how you work with data!
Generating privacy-protected synthetic data using Secludy and MilvusZilliz
During this demo, the founders of Secludy will demonstrate how their system utilizes Milvus to store and manipulate embeddings for generating privacy-protected synthetic data. Their approach not only maintains the confidentiality of the original data but also enhances the utility and scalability of LLMs under privacy constraints. Attendees, including machine learning engineers, data scientists, and data managers, will witness first-hand how Secludy's integration with Milvus empowers organizations to harness the power of LLMs securely and efficiently.
Let's Integrate MuleSoft RPA, COMPOSER, APM with AWS IDP along with Slackshyamraj55
Discover the seamless integration of RPA (Robotic Process Automation), COMPOSER, and APM with AWS IDP enhanced with Slack notifications. Explore how these technologies converge to streamline workflows, optimize performance, and ensure secure access, all while leveraging the power of AWS IDP and real-time communication via Slack notifications.
AI 101: An Introduction to the Basics and Impact of Artificial IntelligenceIndexBug
Imagine a world where machines not only perform tasks but also learn, adapt, and make decisions. This is the promise of Artificial Intelligence (AI), a technology that's not just enhancing our lives but revolutionizing entire industries.
TrustArc Webinar - 2024 Global Privacy SurveyTrustArc
How does your privacy program stack up against your peers? What challenges are privacy teams tackling and prioritizing in 2024?
In the fifth annual Global Privacy Benchmarks Survey, we asked over 1,800 global privacy professionals and business executives to share their perspectives on the current state of privacy inside and outside of their organizations. This year’s report focused on emerging areas of importance for privacy and compliance professionals, including considerations and implications of Artificial Intelligence (AI) technologies, building brand trust, and different approaches for achieving higher privacy competence scores.
See how organizational priorities and strategic approaches to data security and privacy are evolving around the globe.
This webinar will review:
- The top 10 privacy insights from the fifth annual Global Privacy Benchmarks Survey
- The top challenges for privacy leaders, practitioners, and organizations in 2024
- Key themes to consider in developing and maintaining your privacy program
For the full video of this presentation, please visit: https://www.edge-ai-vision.com/2024/06/building-and-scaling-ai-applications-with-the-nx-ai-manager-a-presentation-from-network-optix/
Robin van Emden, Senior Director of Data Science at Network Optix, presents the “Building and Scaling AI Applications with the Nx AI Manager,” tutorial at the May 2024 Embedded Vision Summit.
In this presentation, van Emden covers the basics of scaling edge AI solutions using the Nx tool kit. He emphasizes the process of developing AI models and deploying them globally. He also showcases the conversion of AI models and the creation of effective edge AI pipelines, with a focus on pre-processing, model conversion, selecting the appropriate inference engine for the target hardware and post-processing.
van Emden shows how Nx can simplify the developer’s life and facilitate a rapid transition from concept to production-ready applications.He provides valuable insights into developing scalable and efficient edge AI solutions, with a strong focus on practical implementation.
HCL Notes and Domino License Cost Reduction in the World of DLAUpanagenda
Webinar Recording: https://www.panagenda.com/webinars/hcl-notes-and-domino-license-cost-reduction-in-the-world-of-dlau/
The introduction of DLAU and the CCB & CCX licensing model caused quite a stir in the HCL community. As a Notes and Domino customer, you may have faced challenges with unexpected user counts and license costs. You probably have questions on how this new licensing approach works and how to benefit from it. Most importantly, you likely have budget constraints and want to save money where possible. Don’t worry, we can help with all of this!
We’ll show you how to fix common misconfigurations that cause higher-than-expected user counts, and how to identify accounts which you can deactivate to save money. There are also frequent patterns that can cause unnecessary cost, like using a person document instead of a mail-in for shared mailboxes. We’ll provide examples and solutions for those as well. And naturally we’ll explain the new licensing model.
Join HCL Ambassador Marc Thomas in this webinar with a special guest appearance from Franz Walder. It will give you the tools and know-how to stay on top of what is going on with Domino licensing. You will be able lower your cost through an optimized configuration and keep it low going forward.
These topics will be covered
- Reducing license cost by finding and fixing misconfigurations and superfluous accounts
- How do CCB and CCX licenses really work?
- Understanding the DLAU tool and how to best utilize it
- Tips for common problem areas, like team mailboxes, functional/test users, etc
- Practical examples and best practices to implement right away
Essentials of Automations: The Art of Triggers and Actions in FMESafe Software
In this second installment of our Essentials of Automations webinar series, we’ll explore the landscape of triggers and actions, guiding you through the nuances of authoring and adapting workspaces for seamless automations. Gain an understanding of the full spectrum of triggers and actions available in FME, empowering you to enhance your workspaces for efficient automation.
We’ll kick things off by showcasing the most commonly used event-based triggers, introducing you to various automation workflows like manual triggers, schedules, directory watchers, and more. Plus, see how these elements play out in real scenarios.
Whether you’re tweaking your current setup or building from the ground up, this session will arm you with the tools and insights needed to transform your FME usage into a powerhouse of productivity. Join us to discover effective strategies that simplify complex processes, enhancing your productivity and transforming your data management practices with FME. Let’s turn complexity into clarity and make your workspaces work wonders!
Unlock the Future of Search with MongoDB Atlas_ Vector Search Unleashed.pdfMalak Abu Hammad
Discover how MongoDB Atlas and vector search technology can revolutionize your application's search capabilities. This comprehensive presentation covers:
* What is Vector Search?
* Importance and benefits of vector search
* Practical use cases across various industries
* Step-by-step implementation guide
* Live demos with code snippets
* Enhancing LLM capabilities with vector search
* Best practices and optimization strategies
Perfect for developers, AI enthusiasts, and tech leaders. Learn how to leverage MongoDB Atlas to deliver highly relevant, context-aware search results, transforming your data retrieval process. Stay ahead in tech innovation and maximize the potential of your applications.
#MongoDB #VectorSearch #AI #SemanticSearch #TechInnovation #DataScience #LLM #MachineLearning #SearchTechnology
CAKE: Sharing Slices of Confidential Data on BlockchainClaudio Di Ciccio
Presented at the CAiSE 2024 Forum, Intelligent Information Systems, June 6th, Limassol, Cyprus.
Synopsis: Cooperative information systems typically involve various entities in a collaborative process within a distributed environment. Blockchain technology offers a mechanism for automating such processes, even when only partial trust exists among participants. The data stored on the blockchain is replicated across all nodes in the network, ensuring accessibility to all participants. While this aspect facilitates traceability, integrity, and persistence, it poses challenges for adopting public blockchains in enterprise settings due to confidentiality issues. In this paper, we present a software tool named Control Access via Key Encryption (CAKE), designed to ensure data confidentiality in scenarios involving public blockchains. After outlining its core components and functionalities, we showcase the application of CAKE in the context of a real-world cyber-security project within the logistics domain.
Paper: https://doi.org/10.1007/978-3-031-61000-4_16
Unlocking Productivity: Leveraging the Potential of Copilot in Microsoft 365, a presentation by Christoforos Vlachos, Senior Solutions Manager – Modern Workplace, Uni Systems
Have you ever been confused by the myriad of choices offered by AWS for hosting a website or an API?
Lambda, Elastic Beanstalk, Lightsail, Amplify, S3 (and more!) can each host websites + APIs. But which one should we choose?
Which one is cheapest? Which one is fastest? Which one will scale to meet our needs?
Join me in this session as we dive into each AWS hosting service to determine which one is best for your scenario and explain why!
2. Purpose of the Thesis
• Design and develop tools that could be used for
analyzing discourse in both conversations and
monologues:
– To analyze the main directions in the field of discourse
analysis.
– To identify the main tools to be used in discourse analysis.
– To analyze the role of repetition in discourse.
– To investigate if a repetition-based perspective could be
useful to discourse analysis.
– To develop a theoretical framework that could be used to
analyze both kinds of text: conversations and monologues.
– To build a suite of applications that use the developed
theoretical framework.
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Influence of Repetitions on Discourse and Semantic
Analysis
3. Semantics & Meaning
• Semantics = “the study of how meaning is constructed, interpreted,
clarified, obscured, illustrated, simplified, negotiated, contradicted and
paraphrased” [SMEL].
• Frege (early 1890s): the meaning of a whole context is constructed from
the meaning of its constituent words, also considering the sentence
syntactic structure.
• The meaning of a word is determined by the company it keeps, by the
relations between that word and different linguistic units that are related
to it in a semantic network (network built using semantic means).
• Meaning-representations – formal structures that capture the meaning:
First Order Logic (FOL), Description Logics, Semantic Networks, Frame-
Based Systems, Ontologies.
• Available Resources: WordNet (WN), SentiWordNet, VerbNet (VN),
FrameNet (FN).
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Influence of Repetitions on Discourse and Semantic
Analysis
4. Discourse Analysis – Main Approaches
• Discourse = “a coherent structured group of sentences” [JuMa, 2009].
• Two types of discourses: conversations and monologues.
• Theories in Discourse Analysis:
– J. Hobbs’s Theory – considers a hierarchical organization of the discourse meaning,
starting from some semantic coherence relations that are identified in text. His
theory considers interpretation as abductive inferences in formal logic.
– Grosz et al.’s Theories – also considers that discourse meaning is hierarchical
organized, but starting from the idea of centrality and using two notions
(backward-looking center Cb and forward-looking center Cf) to provide the means of
linking the utterances.
– Rhetorical Structure Theory (RST) – developed by Mann and Thompson, suggests
that the hierarchical structure of discourse can be obtained using a set of rhetorical
relations (such as antithesis, elaboration etc.) to inter-relate the set of text-spans
from the discourse.
– Speech Acts Theory – introduced by Austin and elaborated by Searle, classifies the
discourse utterances according to the action they fulfill.
– Polyphony Theory – based on the idea that in text there are multiple voices that
influence each other.
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Influence of Repetitions on Discourse and Semantic
Analysis
5. Discourse Analysis – Problems of the
Existing Approaches (I)• In the first theories discourse meaning is seen as being incremental, but
discourse tends to be chaotic instead of well organized (topic drifts).
• Problems with Hobbs’s Theory:
– Requires very large DB for encoding the needed information – is domain-
dependent.
– Uses FOL not everything can be represented, inference control (which rule
should be fired and in what order), very computational and time consuming.
– Uses weighted abduction very complicated inference mechanisms, what
common cultural background the participants share.
– Biased towards understanding and establishing coherence in the text.
• Problems with Grosz et al.’s Theories:
– At a given moment, the focus of a discourse is only on a single topic and the switch
between topics is made in a smooth manner.
– The intention for a given segment is the intention of the participant who initiates
that segment.
– The locality of backward-looking center Cb - Cb for an utterance Un is chosen from the
set of forward-looking centers of the previous utterance.
– “Each sentence, S, has a single backward-looking center” [GrJW, 1983].
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Influence of Repetitions on Discourse and Semantic
Analysis
6. Discourse Analysis – Problems of the
Existing Approaches (II)
• Problems with Rhetorical Structure Theory (RST) :
– Had similar problems as the previous theories, but were solved by Potter
(2008) by relaxing the main assumptions of RST: the tree-like rhetorical
structure (graph in fact), uniqueness (one utterance could be involved in
multiple relations), and adjacency constraints (due to chaotic
conversation).
– Disregards the meaning of the words: “Although is better to drink an
airplane, the real solution is the basketball game that flavors politicians
to make high beds.” – has RST structure but is meaningless.
• Problems with Polyphony Theory:
– Has not been applied yet to monologues;
– Doesn’t provide a definition for what can be considered a voice and
therefore the existing frameworks consider them to be either a
participant in the conversation (inconsistence because the content
uttered by a participant is not coherent) or an utterance (that could
answer to multiple previous utterances, therefore being the echo of
different voices incoherence).
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Influence of Repetitions on Discourse and Semantic
Analysis
7. Discourse Analysis – My Adaptation
• Starting from polyphonic framework, we adapted it to work for monologues also,
by considering ideas as voices.
• Considered that a voice is an idea, a concept that is rhythmically repeated in the
analyzed text most of the texts are polyphonic, since usually in text there are
multiple ideas (voices), that flow in parallel, influencing each other, providing
inter-animation.
• Identification of voices: using repetitions (in a larger sense, that will be presented
in the next slides), since according to Brody (1994), a repetition is the echo of what
has been said and it provides a new context for the next uses of the repeated
concept, providing both unity and difference to the discourse (it enhances the
unity-difference axis of a discourse, which is very important for inter-animation).
• Following the repetition threads, one can see if the voices are flowing in parallel,
having a polyphonic text, or they only appear when the others are gone, simply
having multiple monophonic texts. Also, one can see if these voices are influencing
each other (providing inter-animation) or not.
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Influence of Repetitions on Discourse and Semantic
Analysis
8. Repetition
• Tannen (2009) has also noticed the importance of repetition in conversations,
saying that it has 4 different functions in discourse: production, comprehension,
connection and interaction and when all these functions are fulfilled, one can
observe the interpersonal involvement of participants and a coherent
conversation.
• Repetitions classification:
– Who makes the repetition: self-repetition and repetition by others;
– Scale of fixity in form: from exact repetition, to concept repetition with and to
paraphrase;
– Scale of temporality: from immediate repetition, to delayed (diachronic) repetition
within a discourse or across longer periods of time;
– Position of the repeated words in phrase: beginning, end, inverse order, etc.;
– Quantity of repeated information: from a phoneme to a whole sentence or to an idea;
– Intentionality: intentional (consciously used) or unintentional (can derive from
automaticity or different language or cognitive problems).
• We’re interested in the mechanisms that enforce and are able to capture the
inter-animation from a discourse: the unity-difference axis, corresponding to the
criteria: scale of fixity in form and quantity of repeated information.
725.11.2011
Influence of Repetitions on Discourse and Semantic
Analysis
9. Types of Repetitions (I)
• Lexical chains = “sequence of related words in the text” [CaSt, 2001].
– E.g.: London City Capital UK Europe
• Paronymy = words that have similar form, but different meanings.
– usually generated by mistake, lack of knowledge or by the desire to induce a specific rhythm
in the discourse.
• Collocations = “a sequence of two or more words, that has characteristics of a
syntactic and semantic unit, and whose exact and unambiguous meaning or
connotation cannot be derived directly from the meaning or connotation of its
components” [Chou, 1988].
– E.g.: strong tea, to make up, to kick the bucket
– Detected using statistics or by translating in a different language and analyzing if in the new
language the meaning is the same.
• N-grams = a probabilistic model that attempts to identify the next element from a
sequence of elements after we have encountered n-1 elements from it.
– Its parameters are computed from large corpora.
– Usually used in combination with decoding algorithms (such as Viterbi algorithm).
– E.g.: Google Corpus.
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Influence of Repetitions on Discourse and Semantic
Analysis
10. Repetition and Rhythmicity
• The repetition of words, phrases or longer syntactic units determines a
rhythmic pattern that provides musicality and allows for a softer flow of
the discussion – “repetition is rhetorical” [John, 1987].
• The rhythmicity analysis could provide information about identifying:
– the most important concepts presented in a discourse;
– the most important moments of a discourse;
– the combination of concepts that work together;
– the degree of the generality of the debated concepts;
– the artifacts that are built in the discourse and the concepts that they are
related to;
– the right participants (both in numbers and persons) to a conversation that
could ensure a successful collaboration;
– the right sense of a polysemous word.
925.11.2011
11. Applications (I) - Discourse Visualization and the
Identification of the Most Important Moments of it (I)
10
• Develop an application for visualizing the polyphonic analysis of any type of
discourse (conversation or monologue).
• Each “color” represents a voice (an idea) from the discourse.
• Inter-animation = areas where different voices meet they are considered to be
the important moments of the discourse analyzing different voices, one can see
where these important moments are placed in text and can investigate the file if
needed.
• Different types of important moments: pivotal moments, convergence moments,
singular moments, divergence moments and meeting points.
• Flexible application, since the user has the possibility to select what information
he/she wants to be shown.
• The inter-animation analysis also allows the identification of collocations, syntagms
and idioms and of missing links from the database used to build lexical chains.
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12. Applications (I) - Discourse Visualization and the
Identification of the Most Important Moments of it (II)
11
13. Applications (II) - Repetition and Rhythmicity-Based
Assessment Model for Chat Conversations (I)
• We started from our adaptation of the Polyphonic framework, by voice understanding
either a participant or an idea and evaluated the quality of the whole conversation
from the point of view of participants’ involvement in the conversation and by the
effectiveness of the conversation from some given key-concepts points of view.
• We extracted a couple of information from the conversations (how interesting is the
conversation for the users, persistence of the users, explicit connections between the
users’ words, activity of a user, absence of a user, on topic, repetition, usefulness of a
user, topic rhythmicity) and based on them we established some criteria for
evaluating new conversations on the same topic and having the same number of
participants.
• Analyzing different models for different numbers of participants, we have shown that
the models that should be used to evaluate the chats are dependent on the number
of participants: they are different for small (4-5 participants) and medium (6-8
participants) teams, and we expect that these models to also be different for 2-3
participants and for more than 8 participants.
• We have also computed the correlation between the application and the domain
experts at both the validation and verification stages obtaining 0.8389 and
respectively 0.7933 which recommends it as a reliable application.
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14. Applications (II) - Repetition and Rhythmicity-Based
Assessment Model for Chat Conversations (II)
1
Good vs bad
conversation
Application’s
interface
Validation results
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15. Applications (III) - Malapropisms
Detection and Correction
• Develop an application for the detection and correction of malapropos words
(unintentional misuse of a word by confusion with another one).
• Voices represented by the important concepts from the text at some points we
observe dissonances caused by the intervention of a different voice instead of the
voices that would fit in that place.
• Automatically identify these dissonance and solve them:
– Evaluate how probable a combination of words is to be dissonant (using a search engine and
different thresholds);
– See what the dissonant voice would sound like (inspecting the paronyms of the dissonant
voice);
– Replace the dissonant voice with the correct one if this is possible.
• Results for English: between 84% and 87% for malapropism detection, between
68% and 80% for malapropisms correction and around 0.5% rate of introducing
new malapropisms in texts.
• Preliminary tests for Romanian lead to good results, but longer processing time.
We expect that accuracy will be around 70%.
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16. Applications (IV) - Text
Recovery• Improve the quality of OCR, by guessing which are the missing words from the
digital form of the document, using a probabilistic method for text recovery and
the Google n-gram corpus.
• Reconstruction of damaged documents based on the prediction of the most
plausible word sets for filling the missing areas – gaps.
• Two types of voices: voices as concepts and voices as n-grams (since we needed to
also capture the functional words).
• Estimate the document model and then start from the gaps limit and fill the gap
using the most plausible words: preference to the words sets that respected the
document model, contained echoes of the existing voices and were part of more
frequent n-grams in our corpus (more powerful voices).
• The application didn’t achieve the expected results.
• N-grams: not very helpful – coverage rates:
– 5-grams: 15%, 4-grams: 30%, trigrams: 60%, bigrams: 90%
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17. Contributions (I)
• We have made an analysis of the main methods for meaning-
representation used in NLP.
• We have analyzed the main theories from discourse analysis field.
• We have adapted a new theoretical framework, based on the polyphonic
theory, that is domain-independent and that can be used to analyze both
types of discourse, unlike previous approaches to discourse analysis.
• We have presented an analysis of repetitions in conversations, including
the main functions that they have and a classification of repetitions
according to multiple criteria.
• We have investigated the lexical chains building.
• We have developed a new method for building such lexical chains that
also included a disambiguating process.
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18. Contributions (II)
• We have described in detail the concepts of paronymy, collocations, and
n-grams.
• We have built two paronyms dictionary, one for English and one for
Romanian language.
• We have described how the rhythmicity of repetitions could be used in
discourse.
• We have designed and implemented an application for discourse
visualization that works on both conversations and monologues.
• We have proposed a classification of the important moments of a
discourse and a visual method for their identification in discourse. We
have also explained how this method could be used for tasks like
collocation identification or detection of missing links in the used lexical
database.
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19. Contributions (III)
• We have designed an application that could evaluate the quality of a conversation
from the point of view of participants’ involvement in that conversation and by
the effectiveness of the conversation with respect to some given key-concepts.
• We have built an application for malapropism detection and correction, that
worked very well for the English language.
• We have derived an adaptation of the above application in order to make it work
on Romanian language with very good initial results.
• We have described a framework similar to the one used for malapropism
detection and correction that could be used for metaphors’ identification.
• Starting from the Polyphony Theory, we have described a framework that could
help the reconstruction of damaged documents, defining another type of voice
that could be used in the polyphonic framework: the voice as patterns repetition.
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20. Conclusions
• This thesis has addressed a couple of problems from the discourse
analysis domain and has proposed several novel solutions for problems
like discourse visualization, identification of discourse’ important
moments, the assessment of the contribution of the participants to a
CSCL conversation using a rhythmicity-based solution, detection and
correction of malapropisms, generation of text to fill in the gaps from
damaged documents.
• From the theoretical point of view:
– We have proposed a modification of the polyphonic framework that allows
the analysis of any type of discourse (conversation or monologue), starting
from the analysis of the existing approaches and tools from the field of
discourse analysis.
– We have presented the advantages and possible uses provided by the
rhythmicity analysis.
– We have introduced a new type of voice that could be used in the
polyphonic framework: the voice as patterns repetition.
– We have suggested a new method for discourse segmentation.
– We provided a classification of the important moments of a discourse.
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21. Publication list
1. Chiru, C., Trăuşan-Matu, Ş. (2008). Prelucrarea limbajului natural în interacţiunile chat (Romanian), In: Ştefan Trăuşan-Matu (Eds.), Interacţiunea conversaţională în sistemele colaborative pe Web, ISBN 978-
973-755-393-5, Publishing House Matrix Rom, Bucharest, pp. 117-138.
2. Chiru, C., Cojocaru, V., Rebedea, T., Trausan-Matu, S. (2010). Malapropisms Detection and Correction using a Paronyms Dictionary, a Search Engine and WordNet. ICSOFT 2010, vol 2, pp 364-373.
3. Chiru, C., Hanganu, A., Rebedea, T., Trausan-Matu, S. Filling the Gaps using Google 5-Grams corpus. ICSOFT 2010, vol 2, pp 438-443.
4. Chiru, C., Cojocaru, V., Trausan-Matu, S, Rebedea, T., Mihaila, D. (2011). Repetition and Rhythmicity Based Assessment for Chat Conversation. ISMIS 2011, LNAI 6804, Springer, 2011, pp 513-523.
5. Rebedea, T., Trăuşan-Matu, Ş. & Chiru, C. (2008). Extraction of Socio-semantic Data from Chat Conversations in Collaborative Learning Communities. In: Times of Convergence. Technologies Across Learning
Contexts, LNCS Vol. 5192, pp. 366-377, Springer, Berlin.
6. Rebedea, T., Trausan-Matu, S., Chiru, C. (2010). Automatic Feedback System for Collaborative Learning using Chats and Forums. CSEDU (1): 358-363.
7. Rebedea, T., Dascălu, M., Trăuşan-Matu, Ş., Banica, D., Gartner, A., Chiru C. & Mihaila, D. (2010) Overview and Preliminary Results of Using PolyCAFe for Collaboration Analysis and Feedback Generation. In:
Proceedings of ECTEL 2010, LNCS 6283, Springer, pp. 420-425.
8. Rebedea, T., Dascalu, M., Trausan-Matu, S., Armitt, G., & Chiru, C. (2011) Automatic Assessment of Collaborative Chat Conversations with PolyCAFe. ECTEL 2011 (accepted).
9. Scheau, C. Rebedea, T., Chiru, C., Trausan-Matu, S. (2010). Improving the relevance of search engine results by using semantic information from wikipedia. 9th RoEduNet International Conference, pp 151-156.
10. Trausan-Matu S., Posea V., Rebedea T., Chiru C. (2009). Using the Social Web to Supplement Classical Learning. In: Advances in Web Based Learning – ICWL 2009, LNCS 5686, pp. 386-389, Springer.
11. Chiru, C., Trăuşan-Matu, Ş., Rebedea, T. (2008). Algoritmi de generare de paronime pentru corectarea malapropismelor (Romanian). In: Revista Română de Interacţiune Om-Calculator 1 (Vol.1, Nr.1, 2008),
57-72.
12. Chiru, C., Trăuşan-Matu, Ş, Rebedea, T. (2008). O îmbunătăţire a performanţelor algoritmului KNN în sistemele de recomandare pe web. (Romanian). In: Revista Română de Interacţiune Om-Calculator, Vol. 1
(2008) Număr special: Interacţiune Om-Calculator 2008, 41-48.
13. Rebedea, T., Chiru, C., Trăuşan-Matu, Ş. (2008). Portal Web de stiri autonom bazat pe prelucrarea limbajului natural. (Romanian). In: Revista Română de Interacţiune Om-Calculator, Vol. 1 (2008) Număr
special: Interacţiune Om-Calculator 2008, 85-92.
14. Scheau, C. Rebedea, T., Chiru, C., Trausan-Matu, S. (2010). Îmbunătăţirea relevanţei rezultatelor motoarelor de căutare folosind informaţii semantice din Wikipedia. (Romanian). In: Revista Română de
Interacţiune Om-Calculator, Vol. 3 (2010) Număr special: Interacţiune Om-Calculator 2010, 85-90.
15. Chiru, C., Janca, A. & Rebedea, T. (2010). Disambiguation and Lexical Chains Construction using WordNet, S. Trausan-Matu, P.Dessus (Eds.) Natural Language Processing in Support of Learning: Metrics,
Feedback and Connectivity, MatrixRom, pp 65-71.
16. Chiru, C., Rebedea, T. & Ionita, M. (2010). Chat-Adapted POS Tagger for Romanian Language, S. Trausan-Matu, P.Dessus (Eds.) Natural Language Processing in Support of Learning: Metrics, Feedback and
Connectivity, MatrixRom, pp 90-96.
17. Trausan-Matu, S., Karatzas, K. & Chiru, C. (2007). Environmental Information Perception, Analysis and Communication with the Aid of Natural Language Processing. Proceedings of the 21st International
Conference on Informatics for Environmental Protection Environmental Informatics and Systems Research.
18. Trăuşan-Matu, Ş., Dessus, P., Lemaire, B., Mandin, S., Villiot-Leclercq, E., Rebedea, T., Chiru, C., Mihaila, D., Gartner, A., & Zampa, V. (2008). LTfLL - D5.1: Writing support and feedback design. [Online]
http://dspace.ou.nl/bitstream/1820/1700/1/LTfLL_Project_Deliverable_Report_5%201_Final4EC.pdf
19. Trăuşan-Matu, Ş., Dessus, P., Rebedea, T., Mandin, S., Villiot-Leclercq, E., Dascalu, M., Gartner, A., Chiru, C., Banica, D., Mihaila, D., Lemaire, B., Zampa, V., & Graziani, E. (2009). LTfLL - D5.2 Learning support
and feedback. LTfLL-project. [online] http://dspace.ou.nl/bitstream/1820/2251/1/LTfLL_Project_Deliverable_ReportD5%202-final%20EC.pdf
20. Trăuşan-Matu, Ş., Dessus, P., Rebedea, T., Loiseau, M., Dascalu, M., Mihaila, D., Braidman, I., Armitt, G., Smithies, A., Regan, M., Lemaire, B., Stahl, J., Villiot-Leclercq, E., Zampa, V., Chiru, C., Pasov, I., &
Dulceanu, A. (2010). D5.3 Support and feedback services version 1.5. [Online] http://dspace.ou.nl/bitstream/1820/2802/7/D5.3%20final%20EC.pdf
21. Chiru, C. (2007). Unsupervised Cohesion Based Text Segmentation. (2007). In: Proceedings of the EUROLAN 2007 Doctoral Consortium, ISBN 978-973-703-246-1, Publishing House of the “Alexandru Ioan
Cuza” University of Iasi, pp. 93-96.
22. Posea, V., Rebedea, T., Chiru, C., Trăuşan-Matu, Ş. (2012). Social Web Technologies to Enhance Teaching and Learning. In: UPB Scientific Bulletin, (to be published)
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22. Q&A
Thank you for your time!
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Influence of Repetitions on Discourse and Semantic
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