Towards the implementation of a refined data model for a Zulu machine-readable lexicon
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This document discusses refining the data model for a machine-readable Zulu lexicon. It proposes a lexicon update framework using a morphological analyzer and guesser to identify new stems and roots from corpora. A data model is developed representing verbal extensions, deverbatives, and their morphological structures. Native XML and object-oriented databases are considered suitable for implementing the data model due to their ability to represent semi-structured, recursive data and provide different views and sequential access to the morphological information. Future work includes developing and evaluating prototypes for the Zulu lexicon and software to semi-automate the lexicon update framework.
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The document describes an intelligent query processing system for the Malayalam language. It presents a model for developing such a system, focusing on time inquiries for different transportation modes. The system performs shallow syntactic and semantic analysis of queries. It determines the query type and required result slots. SQL queries are generated to retrieve answers from the database. The system architecture includes morphological analysis, shallow parsing, query frame identification, SQL generation, and answer retrieval. It was evaluated on 70 queries with 87.5% precision.
2011linked science4mccuskermcguinnessfinal
Linked Science 2011 talk on the importance of modeling sources and their usage, such as PML's source usage, and how it can be generalized using FRBR
07 04-06
This document discusses cross-language information retrieval (CLIR). It defines CLIR as retrieving information written in a language different from the user's query language. It describes approaches to CLIR such as dictionary-based query translation and pseudo-relevance feedback. Dictionary-based query translation uses bilingual dictionaries but requires disambiguation due to ambiguity. Pseudo-relevance feedback assumes top documents are relevant and selects terms from them to expand the query. The document also discusses using parallel corpora to estimate cross-lingual relevance models and evaluate CLIR using conferences like TREC and CLEF.
Using Semantic and Domain-based Information in CLIR Systems
Cross-Language Information Retrieval (CLIR) systems extend classic information retrieval mechanisms for allowing users to query across languages, i.e., to retrieve documents written in languages different from the language used for query formulation.
In this paper, we present a CLIR system exploiting multilingual ontologies for enriching documents representation with multilingual semantic information during the indexing phase and for mapping query fragments to concepts during the retrieval phase.
This system has been applied on a domain-specific document collection and the contribution of the ontologies to the CLIR system has been evaluated in conjunction with the use of both Microsoft Bing and Google Translate translation services.
Results demonstrate that the use of domain-specific resources leads to a significant improvement of CLIR system performance.
Accessing database using nlp
This document describes a natural language interface for accessing databases. It discusses how natural language processing can be used to allow users to query databases using their own language instead of a specialized query language. It proposes an approach that uses techniques like tokenization, parsing, semantic analysis and query generation to take a natural language query, analyze it, generate a corresponding SQL query, execute it against the database and return results to the user in their own language. The document provides details on the architecture and components of such a natural language interface system and the techniques that can be used to develop it, including pattern matching, syntax-based and semantic-based approaches.
Accessing database using nlp
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
Sem facet paper
The document discusses faceted search over ontology-enhanced RDF data. It formalizes faceted interfaces for querying RDF graphs that capture ontological information. It studies the expressivity and complexity of queries represented by faceted interfaces, and algorithms for generating and updating interfaces based on the underlying RDF and ontology information. The goal is to provide rigorous theoretical foundations for faceted search in the context of RDF and OWL 2 ontologies.
OpenLogos Semantico-Syntactic Knowledge-Rich Bilingual Dictionaries
OpenLogos Semantico-Syntactic Knowledge-Rich Bilingual DictionariesINESC-ID (Spoken Language Systems Laboratory - L2F)
The document describes OpenLogos, an open-source machine translation system that uses knowledge-rich bilingual dictionaries. These dictionaries contain extensive semantic and syntactic information for entries using the Semanic-Syntactic Abstraction Language (SAL). Three English-to-other language dictionaries were created for research purposes containing over 80,000 entries each. The goal is to make the lexical resources freely available to help develop new NLP tools, especially for under-resourced languages.RDF2Rule PRESENTATION
This document discusses RDF2Rule, which is an approach to learning rules from RDF knowledge bases. It does this by first mining frequent predicate cycles (FPCs) from the RDF graphs, which are patterns that frequently appear. It then generates rules from these mined FPCs. RDF2Rule can learn rules quickly from RDF data and always generates more rules than alternative approaches. It also has high quality predictions and fast running times. The document provides background on semantic web issues, RDF, predicate paths and cycles that FPCs are based on, and how RDF2Rule indexes RDF data to efficiently support its mining algorithm.
Research Developments and Directions in Speech Recognition and ...
The document discusses research developments and directions in speech recognition and understanding. It outlines significant developments including improvements to infrastructure like hardware, corpora, and evaluation benchmarks. It also discusses advances in knowledge representation like acoustic features and graph representations, as well as models and algorithms like hidden Markov models and discriminative training. The document proposes six potential "grand challenges" for future research, including creating systems robust to everyday audio variability, rapidly developing speech technologies for emerging languages with limited resources, and enabling spoken language comprehension.
April 8 NISO Webinar: Experimenting with BIBFRAME: Reports from Early Adopters
April 8 NISO Webinar: Experimenting with BIBFRAME: Reports from Early AdoptersNational Information Standards Organization (NISO)
NISO Webinar:
Experimenting with BIBFRAME: Reports from Early Adopters
About the Webinar
In May 2011, the Library of Congress officially launched a new modeling initiative, Bibliographic Framework Initiative, as a linked data alternative to MARC. The Library then announced in November 2012 the proposed model, called BIBFRAME. Since then, the library world is moving from mainly theorizing about the BIBFRAME model to attempts to implement practical experimentation and testing. This experimentation is iterative, and continues to shape the model so that it’s stable enough and broadly acceptable enough for adoption.
In this webinar, several institutions will share their progress in experimenting with BIBFRAME within their library system. They will discuss the existing, developing, and planned projects happening at their institutions. Challenges and opportunities in exploring and implementing BIBFRAME in their institutions will be discussed as well.
Agenda
Introduction
Todd Carpenter, Executive Director, NISO
Experimental Mode: The National Library of Medicine and experiences with BIBFRAME
Nancy Fallgren, Metadata Specialist Librarian, National Library of Medicine, National Institutes of Health, US Department of Health and Human Services (DHHS)
Exploring BIBFRAME at a Small Academic Library
Jeremy Nelson, Metadata and Systems Librarian, Colorado College
Working with BIBFRAME for discovery and production: Linked data for Libraries/Linked Data for Production
Nancy Lorimer, Head, Metadata Dept, Stanford University LibrariesWORD RECOGNITION MASLP
The recognition of spoken word can be viewed as classifying an auditory stimulus to one ‘’word form’’ category, chosen from many alternatives.
This process requires matching of the spoken input with the mental representation associated with the word candidates and selecting one among the several candidates that are atleast partially consistent with the input.
Process of recognizing a spoken word is that it starts from a string of phonemes (Dahan, Magnuson, 2006) establishes how these phonemes should be grouped to form words and passes these words into the next level of processing.
Some theories, though, take a broader view and blur the distinction between speech perception, spoken word recognition, and sentence processing (Elman, 2004; Gaskell & Marslen 1997; Klatt, 1979; McClelland, 1989).
WP3 Further specification of Functionality and Interoperability - Gradmann
The document discusses issues and recommendations for Work Group 3.2 on semantic and multilingual aspects of the Europeana digital library. Key points include:
- Europeana surrogates need rich semantic context in areas like place, time, people and concepts.
- The types of links between surrogates and semantic nodes, as well as the semantic technologies used, need to be determined.
- Support for multiple European languages in areas like search queries, results and functionality is important but requires further scope definition and identification of language resources.
Reasoning on the Semantic Web
The document discusses reasoning on the Semantic Web, including issues, vulnerabilities, and solutions. It covers work done so far in ontologies and rules, points out vulnerabilities like lack of referential integrity and inconsistent knowledge from multiple resources. It discusses the need for reasoners to be incomplete but possibly unsound to handle the scale of the web. Related work in distributed reasoning is presented, and it concludes by looking forward to the need for web-scale reasoning that can deal with incomplete and inconsistent resources while being context-aware and allowing different representations of open and closed world assumptions.
USING TF-ISF WITH LOCAL CONTEXT TO GENERATE AN OWL DOCUMENT REPRESENTATION FO...
In this paper we combine our previous research in the field of Semantic web, especially ontology learning and population with Sentence retrieval. To do this we developed a new approach to sentence retrieval
modifying our previous TF-ISF method which uses local context information to take into account only document level information. This is quite a new approach to sentence retrieval, presented for the first time
in this paper and also compared to the existing methods that use information from whole document collection. Using this approach and developed methods for sentence retrieval on a document level it is possible to assess the relevance of a sentence by using only the information from the retrieved sentence’s document and to define a document level OWL representation for sentence retrieval that can be
automatically populated. In this way the idea of Semantic Web through automatic and semi-automatic
extraction of additional information from existing web resources is supported. Additional information is
formatted in OWL document containing document sentence relevance for sentence retrieval.
Benchmarking Versioning for Big Linked Data
The document discusses benchmarking versioning systems for big linked data. It describes the need for versioning benchmarks that test how systems perform with respect to storage space required for multiversion repositories and efficiency of retrieving different versions and answering cross-snapshot queries. It outlines approaches for versioning like full materialization, delta-based, and timestamped tuples. The document also lists several linked data stores with versioning capabilities and notes the complete lack of existing versioning benchmarks. It proposes the design of a versioning benchmark for the HOBBIT project that would generate versions based on changes observed in evolving datasets and include cross-snapshot queries to evaluate system performance.
Presentation of HOBBIT's versioning benchmark at Graph-TA
HOBBIT's versioning benchmark at Graph-TA.
(This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 688227.)
Matching and merging anonymous terms from web sources
This paper describes a workflow of simplifying and matching spec This paper describes a workflow of simplifying and matching spec This paper describes a workflow of simplifying and matching specThis paper describes a workflow of simplifying and matching specThis paper describes a workflow of simplifying and matching specThis paper describes a workflow of simplifying and matching specThis paper describes a workflow of simplifying and matching spec This paper describes a workflow of simplifying and matching specThis paper describes a workflow of simplifying and matching spec This paper describes a workflow of simplifying and matching spec This paper describes a workflow of simplifying and matching spec This paper describes a workflow of simplifying and matching specThis paper describes a workflow of simplifying and matching specThis paper describes a workflow of simplifying and matching specThis paper describes a workflow of simplifying and matching specThis paper describes a workflow of simplifying and matching specThis paper describes a workflow of simplifying and matching specThis paper describes a workflow of simplifying and matching spec This paper describes a workflow of simplifying and matching spec This paper describes a workflow of simplifying and matching specThis paper describes a workflow of simplifying and matching specThis paper describes a workflow of simplifying and matching specThis paper describes a workflow of simplifying and matching spec This paper describes a workflow of simplifying and matching specThis paper describes a workflow of simplifying and matching specThis paper describes a workflow of simplifying and matching spec This paper describes a workflow of simplifying and matching spec This paper describes a workflow of simplifying and matching specThis paper describes a workflow of simplifying and matching specThis paper describes a workflow of simplifying and matching specThis paper describes a workflow of simplifying and matching specThis paper describes a workflow of simplifying and matching specThis paper describes a workflow of simplifying and matching specThis paper describes a workflow of simplifying and matching spec This paper describes a workflow of simplifying and matching spec This paper describes a workflow of simplifying and matching spec This paper describes a workflow of simplifying and matching specThis paper describes a workflow of simplifying and matching specThis paper describes a workflow of simplifying and matching specThis paper describes a workflow of simplifying and matching specThis paper describes a workflow of simplifying and matching spec ial language terms in RDF generated ial language terms in RDF generated ial language terms in RDF generated ial language terms in RDF generated ial language terms in RDF generated ial language terms in RDF generated ial language terms in RDF generated ial language terms in RDF generated ial language terms in RDF generated ial language terms in RDF generated i
Recent advances in LVCSR : A benchmark comparison of performances
Large Vocabulary Continuous Speech Recognition (LVCSR), which is characterized by a high variability of the speech, is the most challenging task in automatic speech recognition (ASR). Believing that the evaluation of ASR systems on relevant and common speech corpora is one of the key factors that help accelerating research, we present, in this paper, a benchmark comparison of the performances of the current state-of-the-art LVCSR systems over different speech recognition tasks. Furthermore, we put objectively into evidence the best performing technologies and the best accuracy achieved so far in each task. The benchmarks have shown that the Deep Neural Networks and Convolutional Neural Networks have proven their efficiency on several LVCSR tasks by outperforming the traditional Hidden Markov Models and Guaussian Mixture Models. They have also shown that despite the satisfying performances in some LVCSR tasks, the problem of large-vocabulary speech recognition is far from being solved in some others, where more research efforts are still needed.
Named Entity Recognition using Hidden Markov Model (HMM)
Named Entity Recognition (NER) is the subtask of Natural Language Processing (NLP) which is the branch
of artificial intelligence. It has many applications mainly in machine translation, text to speech synthesis,
natural language understanding, Information Extraction, Information retrieval, question answering etc.
The aim of NER is to classify words into some predefined categories like location name, person name,
organization name, date, time etc. In this paper we describe the Hidden Markov Model (HMM) based
approach of machine learning in detail to identify the named entities. The main idea behind the use of
HMM model for building NER system is that it is language independent and we can apply this system for
any language domain. In our NER system the states are not fixed means it is of dynamic in nature one can
use it according to their interest. The corpus used by our NER system is also not domain specific.
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Using Semantic and Domain-based Information in CLIR Systems
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OpenLogos Semantico-Syntactic Knowledge-Rich Bilingual Dictionaries
Research Developments and Directions in Speech Recognition and ...
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April 8 NISO Webinar: Experimenting with BIBFRAME: Reports from Early Adopters
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USING TF-ISF WITH LOCAL CONTEXT TO GENERATE AN OWL DOCUMENT REPRESENTATION FO...
Presentation of HOBBIT's versioning benchmark at Graph-TA
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Matching and merging anonymous terms from web sources
Matching and merging anonymous terms from web sources
Recent advances in LVCSR : A benchmark comparison of performances
Recent advances in LVCSR : A benchmark comparison of performances
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2) Creating corpora of Creole language texts from literary, educational and journalistic sources online
3) Maintaining the dictionary by analyzing the corpora to identify unknown words and improve the database through an iterative process.
The results will be a lexicographical database detailing variations in French-based Creoles and an annotated corpora for linguistic research.
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This document summarizes research that semi-automatically extracted a morphological grammar for Southern Ndebele, an under-resourced language, from a general Nguni morphological analyzer bootstrapped from a Zulu analyzer. The Southern Ndebele analyzer produced surprisingly good results, showing significant similarities across Nguni languages that can accelerate documentation and resource development for these languages. The project followed best practices for encoding resources to ensure sustainability, access, and adaptability to future formats and platforms.
Resource-Light Bantu Part-of-Speech Tagging
This document proposes a bag-of-substrings approach to part-of-speech tagging for under-resourced Bantu languages using available digital dictionaries and word lists instead of large annotated corpora. Experimental results showed the technique established a low-resource, high accuracy method for bootstrapping POS tagging that compares favorably to state-of-the-art data-driven approaches. The method extracts substring features from words to train a maximum entropy classifier and bootstrap POS tagging for Bantu languages that lack extensive annotated resources.
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POS Annotated 50m Corpus of Tajik Language
This document presents a new 50+ million word corpus of the Tajik language, the largest available. It was created by crawling over a dozen Tajik news websites and other sources. The texts were joined and cleaned to remove duplicates. The corpus was then annotated with morphological analysis of Tajik using a new analyzer created by modifying an existing one to be faster and allow lemmatization. The analyzer recognizes over 87% of words and tags them with part of speech. This annotated corpus containing lemmas, tags and frequencies is available online through the Sketch Engine for researchers.
The Tagged Icelandic Corpus (MÍM)
© Sigrún Helgadóttir, Ásta Svavarsdóttir, Eiríkur Rögnvaldsson, Kristín Bjarnadóttir and Hrafn Loftsson
Describing Morphologically Rich Languages Using Metagrammars a Look at Verbs ...
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Tagging and Verifying an Amharic News Corpus
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Automatic Structuring and Correction Suggestion System for Hungarian Clinical...
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The Database of Modern Icelandic Inflection
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How to build language technology resources for the next 100 years
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Towards Standardizing Evaluation Test Sets for Compound Analysers
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The PALDO Concept - New Paradigms for African Language Resource Development
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A System for the Recognition of Handwritten Yorùbá Characters
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IFE-MT: An English-to-Yorùbá Machine Translation System
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A Number to Yorùbá Text Transcription System
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Towards the implementation of a refined data model for a Zulu machine-readable lexicon
- 1. Towards the implementation of a refined data model for a zulu machine-readable lexicon Ronell van der Merwe Laurette Pretorius Sonja Bosch 1
- 2. Goal ... to develop .... a complete data repository (database) Bantu languages Machine Readable (MR) lexicon applications: finite state morphological analyser, .... 2
- 3. What we will be discussing .... Brief overview Lexicon update framework Data model Implementation approaches Conclusion Future work 3
- 4. 1. Introduction - Comprehensive MR lexicon Update framework ZULU corpora Paper Dict 4
- 5. 2. Lexicon Update Framework Morphological Analyser ZulMorph Corpus apply failures successes rebuild Guesser MR lexicon update new stems/roots 5
- 6. Purpose of MR Lexicon MorphologicalAnalyser Apps ZulMorph MR lexicon used Repository of all lexical information re-used Apps 6 Morphosyntactic information: Zulu morphotactics Morphophonological alternation rules Embedded stem/root lexicon
- 7. Guesser variant Phonologically possible stems /roots Guesser identify new candidate(s) MR lexicon update / include 7
- 8. 3. Data Model - development 8 * 0 or more + 1 or more | optional leaf node
- 9. 3.1 Verbal extensions Suffixing extensions to verb root: Applied Causative Intensive Neuter Passive Reciprocal 9 * 0 or more + 1 or more | optional leaf node
- 10. 10
- 11. 11
- 12. 12
- 13. 3.2 Deverbatives verb / extended verb root noun class prefix deverbative suffix (-o- | -i- |-a-| -e-| -u-) 13 optional: nominal suffix (Aug | Dim | Loc | Fem)
- 14. 14
- 15. 15
- 16. 4. Towards implementation 16 Morphological Analyser ZulMorph MR lexicon The capturing of the data must be: rigorous systematic appropriately structured To ensure that: data exchange is consistent
- 17. Considerations in the choice of database... type of data different views of data different types of access to data 17
- 18. Consideration: Type of Data semi-structured allows for recursion n-depth structures 18
- 19. Consideration: views and access Rebuilding the Morphological Analyser: view: morphological structure of all word roots/stems access: sequential 19
- 20. XML – enabled database 20 Object-Oriented Database Relational Database <root>bon</root> <verbfeatures> ....... </verbfeatures>
- 21. Native XML database (NXD) 21 Native XML DB XQuery XUpdate <root>bon</root> <verbfeatures> ....... </verbfeatures>
- 23. NXD and OO Database satisfy the implementation considerations: Both ... are suitable for our type of data: semi-structured , recursive satisfy the type of access and view: sequential access to morphological information of all word roots/stems 23
- 24. Conclusion Refinement of a data model for the Zulu MR lexicon verbal extensions and deverbatives MR Lexicon embedded in an update framework Native XML and OO Databases possible approaches to implementation 24
- 25. Future work Development and evaluation of prototypes for the MR Lexicon (Zulu) Software for semi-automating the lexicon update framework Bootstrapping of MR Lexicon for other Bantu languages 25