This workshop introduces two user-friendly applications, namely Language Variation Suite and Interactive Text Mining Suite, that allow researchers visually explore and statistically analyze language data. Written in R with Shiny app, these applications not only provide a web interactive interface, they also allow researchers implement state-of-the-art statistical methods, such as cluster analysis, topic modeling, inferential trees and mixed model logistic regressions.
This document outlines a process for preparing reports in various file formats like PDF, Word, and PowerPoint with embedded R code. The process involves opening a file, writing content, embedding R code, rendering the output, and saving the final report.
Introducing R Shiny and R notebook: R collaborative toolsXavier Prudent
This document discusses how to improve performance and reproducibility in R using R Notebooks and R Shiny. It provides an overview and instructions for creating R Notebooks and R Shiny apps. R Notebooks allow incorporating R code, outputs, plots and comments into a single document. R Shiny allows building interactive web apps with R by separating the user interface from the backend code. The document demonstrates how to set up basic R Notebooks and R Shiny apps and enhance them with features like commenting, tables, formatting and interactivity.
This document provides an introduction to R Markdown. It explains that R Markdown combines Markdown syntax and R code chunks to create dynamic reports and documents. The document outlines the key topics that will be covered, including what Markdown and R Markdown are, Markdown syntax like headers, emphasis, lists, links and images, R code chunks and options, and RStudio settings. Resources for learning more about Markdown, R Markdown, and related tools are provided.
Data Visualization: Introduction to Shiny Web ApplicationsOlga Scrivner
In this workshop, I will introduce you to the concept of Declarative Reactive Web Frameworks, allowing for interactive user-friendly data visualization and data analytics, particularly Shiny. Shiny is an R package that creates interactive applications for data visualization. You will learn some Shiny basics: how to build your reactive app and deploy it to the server
Workshop on Quantitative Analytics Using Interactive On-line ToolOlga Scrivner
This document provides an overview of the Language Variation Suite (LVS), an interactive web application for visual data analysis. The summary outlines key sections of the document:
1. LVS allows users to upload data files, perform summary statistics, cross tabulation, data adjustment, and visual and inferential analysis.
2. Visual analysis in LVS includes plotting variables, customizing plots, saving plots, and cluster classification.
3. Inferential analysis in LVS includes regression modeling, comparing regression models, and conditional tree analysis to capture variable interactions.
This document outlines a process for preparing reports in various file formats like PDF, Word, and PowerPoint with embedded R code. The process involves opening a file, writing content, embedding R code, rendering the output, and saving the final report.
Introducing R Shiny and R notebook: R collaborative toolsXavier Prudent
This document discusses how to improve performance and reproducibility in R using R Notebooks and R Shiny. It provides an overview and instructions for creating R Notebooks and R Shiny apps. R Notebooks allow incorporating R code, outputs, plots and comments into a single document. R Shiny allows building interactive web apps with R by separating the user interface from the backend code. The document demonstrates how to set up basic R Notebooks and R Shiny apps and enhance them with features like commenting, tables, formatting and interactivity.
This document provides an introduction to R Markdown. It explains that R Markdown combines Markdown syntax and R code chunks to create dynamic reports and documents. The document outlines the key topics that will be covered, including what Markdown and R Markdown are, Markdown syntax like headers, emphasis, lists, links and images, R code chunks and options, and RStudio settings. Resources for learning more about Markdown, R Markdown, and related tools are provided.
Data Visualization: Introduction to Shiny Web ApplicationsOlga Scrivner
In this workshop, I will introduce you to the concept of Declarative Reactive Web Frameworks, allowing for interactive user-friendly data visualization and data analytics, particularly Shiny. Shiny is an R package that creates interactive applications for data visualization. You will learn some Shiny basics: how to build your reactive app and deploy it to the server
Workshop on Quantitative Analytics Using Interactive On-line ToolOlga Scrivner
This document provides an overview of the Language Variation Suite (LVS), an interactive web application for visual data analysis. The summary outlines key sections of the document:
1. LVS allows users to upload data files, perform summary statistics, cross tabulation, data adjustment, and visual and inferential analysis.
2. Visual analysis in LVS includes plotting variables, customizing plots, saving plots, and cluster classification.
3. Inferential analysis in LVS includes regression modeling, comparing regression models, and conditional tree analysis to capture variable interactions.
This document discusses speech analytics and its use for analyzing customer call center conversations. It begins by explaining the challenges of analyzing speech data and how speech recognition systems work to transform speech into structured data. It then discusses common use cases for speech analytics in call centers, such as sentiment analysis and agent performance monitoring. Next, it provides an overview of major vendors in the speech analytics market. It proposes a two-phase architecture for speech analytics involving speech recognition and predictive analytics. Finally, it presents a case study using speech analytics to predict customer loyalty scores for a health insurance provider.
IMPROVING DIALOGUE MANAGEMENT THROUGH DATA OPTIMIZATIONkevig
In task-oriented dialogue systems, the ability for users to effortlessly communicate with machines and
computers through natural language stands as a critical advancement. Central to these systems is the
dialogue manager, a pivotal component tasked with navigating the conversation to effectively meet user
goals by selecting the most appropriate response. Traditionally, the development of sophisticated dialogue
management has embraced a variety of methodologies, including rule-based systems, reinforcement
learning, and supervised learning, all aimed at optimizing response selection in light of user inputs. This
research casts a spotlight on the pivotal role of data quality in enhancing the performance of dialogue
managers. Through a detailed examination of prevalent errors within acclaimed datasets, such as
Multiwoz 2.1 and SGD, we introduce an innovative synthetic dialogue generator designed to control the
introduction of errors precisely. Our comprehensive analysis underscores the critical impact of dataset
imperfections, especially mislabeling, on the challenges inherent in refining dialogue management
processes.
Improving Dialogue Management Through Data Optimizationkevig
In task-oriented dialogue systems, the ability for users to effortlessly communicate with machines and computers through natural language stands as a critical advancement. Central to these systems is the dialogue manager, a pivotal component tasked with navigating the conversation to effectively meet user goals by selecting the most appropriate response. Traditionally, the development of sophisticated dialogue management has embraced a variety of methodologies, including rule-based systems, reinforcement learning, and supervised learning, all aimed at optimizing response selection in light of user inputs. This research casts a spotlight on the pivotal role of data quality in enhancing the performance of dialogue managers. Through a detailed examination of prevalent errors within acclaimed datasets, such as Multiwoz 2.1 and SGD, we introduce an innovative synthetic dialogue generator designed to control the introduction of errors precisely. Our comprehensive analysis underscores the critical impact of dataset imperfections, especially mislabeling, on the challenges inherent in refining dialogue management processes.
Improving Software Maintenance using Unsupervised Machine Learning techniquesValerio Maggio
"Improving Software Maintenance using Unsupervised Machine Learning techniques": Ph.D. defence presentation.
Unsupervised Machine Learning techniques have been used to face different software maintenance issues such as Software Modularisation and Clone detection.
Tutorial given at RANLP 2015 in Hissar, Bulgaria
Recent years have seen lots of changes in the field of computational linguistics, most of them due to the widespread use of the Internet and the benefits and problems it brings. The first part of this tutorial will discuss these changes and will focus on crowdsourcing and how it influenced the creation of annotated data.
Annotation of data employed to train and test NLP methods used to be the task of language experts who had a good understanding of the linguistic phenomena to be tackled. Given that a large number of people now have access to the Internet, crowdsourcing has become an alternative way of obtaining annotated data. The core idea of crowdsourcing is that it is possible to design tasks that can be completed by non-experts and that the outputs of these tasks can be combined to obtain high-quality linguistic annotation, which would normally be produced by experts. Examples of how crowdsourcing was employed in computational linguistics will be given.
Big data is another trend in computational linguistics as researchers rely on more and more data for improving the results of a method. The second part of the tutorial will introduce the MapReduce programming model and show how it was used in processing language. Combined with processing larger quantities of data, the field of computational linguistics has applied deep learning to various tasks successfully, improving their accuracy. An introduction to deep learning will be provided, followed by examples of how it was applied to tasks such as learning semantic representations, sentiment analysis and machine translation evaluation.
The document discusses the development of an open source platform called My Web Intelligence to support digital humanities research. It aims to unify the many separate projects through a single platform, ensure open governance from the start through collaborative tools, and benefit the common good by being easy to install and well documented. The platform will extract and archive large amounts of data from heterogeneous sources, provide tools for corpus management, and automate the analysis and qualification of content through techniques like natural language processing.
French machine reading for question answeringAli Kabbadj
This paper proposes to unlock the main barrier to machine reading and comprehension French natural language texts. This open the way to machine to find to a question a precise answer buried in the mass of unstructured French texts. Or to create a universal French chatbot. Deep learning has produced extremely promising results for various tasks in natural language understanding particularly topic classification, sentiment analysis, question answering, and language translation. But to be effective Deep Learning methods need very large training da-tasets. Until now these technics cannot be actually used for French texts Question Answering (Q&A) applications since there was not a large Q&A training dataset. We produced a large (100 000+) French training Dataset for Q&A by translating and adapting the English SQuAD v1.1 Dataset, a GloVe French word and character embed-ding vectors from Wikipedia French Dump. We trained and evaluated of three different Q&A neural network ar-chitectures in French and carried out a French Q&A models with F1 score around 70%.
This document discusses the different database options for handling big data: SQL, HBase, Hive, and Spark. SQL databases are not well-suited for big data due to limitations in scalability. HBase is a non-SQL database that can handle large volumes of data across clusters but lacks querying capabilities. Hive provides SQL-like querying of large datasets but is slower than other options. Spark can be used for both batch processing and interactive queries, making it a flexible option for big data workloads. The best choice depends on an application's specific needs and tradeoffs among performance, scalability, and functionality.
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
Semantic Web: Technolgies and Applications for Real-WorldAmit Sheth
Amit Sheth and Susie Stephens, "Semantic Web: Technolgies and Applications for Real-World," Tutorial at 2007 World Wide Web Conference, Banff, Canada.
Tutorial discusses technologies and deployed real-world applications through 2007.
Tutorial description at: http://www2007.org/tutorial-T11.php
In this talk I will address issues of "rigour" and "quality" in qualitative research, and the way that the two are closely aligned with how the researcher may explore various points of focus within the research process itself. Rigour and quality are inseparable from the generative nature of much qualitative inquiry, and the need to "show your workings" in the field within which the research is carried out. I will discuss this using examples of particular aspects of qualitative research that I have been involved with recently, both in design and execution. I will also discuss the opportunities and challenges of making a case for qualitative insights to augment and add value to other forms of research.
hExarAbax makkAmasjix samayaM anni rojulu 5:00 am - 9:00 pm
(Mecca Masjid timings in Hyderabad - All days 5:00 am - 9:00 pm)
User query: makkAmasjix PIju eVMwa?
(What is the fee for Mecca Masjid?)
POS-tagger: makkAmasjix PIju/WQ eVMwa
Replace with root word: makkAmasjix PIju/WQ eMwa
Context Handler: Updates context to 'makkAmasjix'
Advanced Filter: Keywords - makkAmas
COMPREHENSIVE ANALYSIS OF NATURAL LANGUAGE PROCESSING TECHNIQUEJournal For Research
Natural Language Processing (NLP) techniques are one of the most used techniques in the field of computer applications. It has become one of the vast and advanced techniques. Language is the means of communication or interaction among humans and in present scenario when everything is dependent on machine or everything is computerized, communication between computer and human has become a necessity. To fulfill this necessity NLP has been emerged as the means of interaction which narrows the gap between machines (computers) and humans. It was evolved from the study of linguistics which was passed through the Turing test to check the similarity between data but it was limited to small set of data. Later on various algorithms were developed along with the concept of AI (Artificial Intelligence) for the successful execution of NLP. In this paper, the main emphasis is on the different techniques of NLP which have been developed till now, their applications and the comparison of all those techniques on different parameters.
Embracing Social Software And Semantic Web In Digital LibrariesAkhmad Riza Faizal
1) The document discusses social software and semantic web technologies in digital libraries based on a literature review. It describes various social software tools and their usage in research libraries.
2) It also discusses recommendations and challenges regarding personalization in digital libraries, including modeling users, balancing personal and community needs, and evaluating social effects.
3) The use of open source systems like WordPress to customize digital library interfaces is presented, along with issues in managing library data and skills.
4) Examples of mobile social software and semantic digital libraries are provided, with definitions and differences between conventional and semantic digital libraries.
WP3 Further specification of Functionality and Interoperability - GradmannEuropeana
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.
Data Science Tools and Technologies: A Comprehensive Overviewsaniakhan8105
"Data Science Tools and Technologies: A Comprehensive Overview" explores the essential tools and platforms that data scientists use to analyze, visualize, and interpret complex data. From programming languages like Python and R to advanced frameworks like TensorFlow and Hadoop, this guide covers everything needed for effective data science practice.
Arabic SentiWordNet in Relation to SentiWordNet 3.0Waqas Tariq
Sentiment analysis and opinion mining are the tasks of identifying positive or negative opinions and emotions from pieces of text. The SentiWordNet (SWN) plays an important role in extracting opinions from texts. It is a publicly available sentiment measuring tool used in sentiment classification and opinion mining. We firstly discuss the development of the English SWN for versions 1.0 and 3.0. This is to provide the basis for developing an equivalent SWN for the Arabic language through a mapping to the latest version of the English SWN 3.0. We also discuss the construction of an annotated sentiment corpus for Arabic and its relationship to the Arabic SWN.
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.
A NOVEL APPROACH OF CLASSIFICATION TECHNIQUES FOR CLIRcscpconf
Recent and continuing advances in online information systems are creating many opportunities
and also new problems in information retrieval. Gathering the information in different natural
language is the most difficult task, which often requires huge resources. Cross-language
information retrieval (CLIR) is the retrieval of information for a query written in the native
language. This paper deals with various classification techniques that can be used for solving
the problems encountered in CLIR.
Engaging Students Competition and Polls.pptxOlga Scrivner
The document discusses strategies for improving student engagement in online learning settings. It suggests that tools like polls, surveys, and competitive games through platforms like Poll Everywhere and Quizlet can enhance student connectedness and engagement. When students are more engaged through interactive activities, they exhibit stronger course achievement and higher graduation rates. The document provides an overview of Poll Everywhere and Quizlet as examples of online tools that faculty can utilize to build class unity and foster in-depth thought among students in an online environment.
HICSS ATLT: Advances in Teaching and Learning TechnologiesOlga Scrivner
The document summarizes recent research presented at the Hawaii International Conference on System Sciences related to using virtual and augmented reality technologies in education. Key points discussed include the potential of these technologies to enhance learning through immersive experiences, interaction, and customized instruction. Several studies examined how virtual reality can support different levels of learning and topics. Design principles for virtual reality learning emphasized aligning the technology with learning objectives and incorporating interactivity, motivation, and multi-sensory experiences.
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Similar to Data Visualization: Language Variation Suite and Interactive Text Mining Suite
This document discusses speech analytics and its use for analyzing customer call center conversations. It begins by explaining the challenges of analyzing speech data and how speech recognition systems work to transform speech into structured data. It then discusses common use cases for speech analytics in call centers, such as sentiment analysis and agent performance monitoring. Next, it provides an overview of major vendors in the speech analytics market. It proposes a two-phase architecture for speech analytics involving speech recognition and predictive analytics. Finally, it presents a case study using speech analytics to predict customer loyalty scores for a health insurance provider.
IMPROVING DIALOGUE MANAGEMENT THROUGH DATA OPTIMIZATIONkevig
In task-oriented dialogue systems, the ability for users to effortlessly communicate with machines and
computers through natural language stands as a critical advancement. Central to these systems is the
dialogue manager, a pivotal component tasked with navigating the conversation to effectively meet user
goals by selecting the most appropriate response. Traditionally, the development of sophisticated dialogue
management has embraced a variety of methodologies, including rule-based systems, reinforcement
learning, and supervised learning, all aimed at optimizing response selection in light of user inputs. This
research casts a spotlight on the pivotal role of data quality in enhancing the performance of dialogue
managers. Through a detailed examination of prevalent errors within acclaimed datasets, such as
Multiwoz 2.1 and SGD, we introduce an innovative synthetic dialogue generator designed to control the
introduction of errors precisely. Our comprehensive analysis underscores the critical impact of dataset
imperfections, especially mislabeling, on the challenges inherent in refining dialogue management
processes.
Improving Dialogue Management Through Data Optimizationkevig
In task-oriented dialogue systems, the ability for users to effortlessly communicate with machines and computers through natural language stands as a critical advancement. Central to these systems is the dialogue manager, a pivotal component tasked with navigating the conversation to effectively meet user goals by selecting the most appropriate response. Traditionally, the development of sophisticated dialogue management has embraced a variety of methodologies, including rule-based systems, reinforcement learning, and supervised learning, all aimed at optimizing response selection in light of user inputs. This research casts a spotlight on the pivotal role of data quality in enhancing the performance of dialogue managers. Through a detailed examination of prevalent errors within acclaimed datasets, such as Multiwoz 2.1 and SGD, we introduce an innovative synthetic dialogue generator designed to control the introduction of errors precisely. Our comprehensive analysis underscores the critical impact of dataset imperfections, especially mislabeling, on the challenges inherent in refining dialogue management processes.
Improving Software Maintenance using Unsupervised Machine Learning techniquesValerio Maggio
"Improving Software Maintenance using Unsupervised Machine Learning techniques": Ph.D. defence presentation.
Unsupervised Machine Learning techniques have been used to face different software maintenance issues such as Software Modularisation and Clone detection.
Tutorial given at RANLP 2015 in Hissar, Bulgaria
Recent years have seen lots of changes in the field of computational linguistics, most of them due to the widespread use of the Internet and the benefits and problems it brings. The first part of this tutorial will discuss these changes and will focus on crowdsourcing and how it influenced the creation of annotated data.
Annotation of data employed to train and test NLP methods used to be the task of language experts who had a good understanding of the linguistic phenomena to be tackled. Given that a large number of people now have access to the Internet, crowdsourcing has become an alternative way of obtaining annotated data. The core idea of crowdsourcing is that it is possible to design tasks that can be completed by non-experts and that the outputs of these tasks can be combined to obtain high-quality linguistic annotation, which would normally be produced by experts. Examples of how crowdsourcing was employed in computational linguistics will be given.
Big data is another trend in computational linguistics as researchers rely on more and more data for improving the results of a method. The second part of the tutorial will introduce the MapReduce programming model and show how it was used in processing language. Combined with processing larger quantities of data, the field of computational linguistics has applied deep learning to various tasks successfully, improving their accuracy. An introduction to deep learning will be provided, followed by examples of how it was applied to tasks such as learning semantic representations, sentiment analysis and machine translation evaluation.
The document discusses the development of an open source platform called My Web Intelligence to support digital humanities research. It aims to unify the many separate projects through a single platform, ensure open governance from the start through collaborative tools, and benefit the common good by being easy to install and well documented. The platform will extract and archive large amounts of data from heterogeneous sources, provide tools for corpus management, and automate the analysis and qualification of content through techniques like natural language processing.
French machine reading for question answeringAli Kabbadj
This paper proposes to unlock the main barrier to machine reading and comprehension French natural language texts. This open the way to machine to find to a question a precise answer buried in the mass of unstructured French texts. Or to create a universal French chatbot. Deep learning has produced extremely promising results for various tasks in natural language understanding particularly topic classification, sentiment analysis, question answering, and language translation. But to be effective Deep Learning methods need very large training da-tasets. Until now these technics cannot be actually used for French texts Question Answering (Q&A) applications since there was not a large Q&A training dataset. We produced a large (100 000+) French training Dataset for Q&A by translating and adapting the English SQuAD v1.1 Dataset, a GloVe French word and character embed-ding vectors from Wikipedia French Dump. We trained and evaluated of three different Q&A neural network ar-chitectures in French and carried out a French Q&A models with F1 score around 70%.
This document discusses the different database options for handling big data: SQL, HBase, Hive, and Spark. SQL databases are not well-suited for big data due to limitations in scalability. HBase is a non-SQL database that can handle large volumes of data across clusters but lacks querying capabilities. Hive provides SQL-like querying of large datasets but is slower than other options. Spark can be used for both batch processing and interactive queries, making it a flexible option for big data workloads. The best choice depends on an application's specific needs and tradeoffs among performance, scalability, and functionality.
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
Semantic Web: Technolgies and Applications for Real-WorldAmit Sheth
Amit Sheth and Susie Stephens, "Semantic Web: Technolgies and Applications for Real-World," Tutorial at 2007 World Wide Web Conference, Banff, Canada.
Tutorial discusses technologies and deployed real-world applications through 2007.
Tutorial description at: http://www2007.org/tutorial-T11.php
In this talk I will address issues of "rigour" and "quality" in qualitative research, and the way that the two are closely aligned with how the researcher may explore various points of focus within the research process itself. Rigour and quality are inseparable from the generative nature of much qualitative inquiry, and the need to "show your workings" in the field within which the research is carried out. I will discuss this using examples of particular aspects of qualitative research that I have been involved with recently, both in design and execution. I will also discuss the opportunities and challenges of making a case for qualitative insights to augment and add value to other forms of research.
hExarAbax makkAmasjix samayaM anni rojulu 5:00 am - 9:00 pm
(Mecca Masjid timings in Hyderabad - All days 5:00 am - 9:00 pm)
User query: makkAmasjix PIju eVMwa?
(What is the fee for Mecca Masjid?)
POS-tagger: makkAmasjix PIju/WQ eVMwa
Replace with root word: makkAmasjix PIju/WQ eMwa
Context Handler: Updates context to 'makkAmasjix'
Advanced Filter: Keywords - makkAmas
COMPREHENSIVE ANALYSIS OF NATURAL LANGUAGE PROCESSING TECHNIQUEJournal For Research
Natural Language Processing (NLP) techniques are one of the most used techniques in the field of computer applications. It has become one of the vast and advanced techniques. Language is the means of communication or interaction among humans and in present scenario when everything is dependent on machine or everything is computerized, communication between computer and human has become a necessity. To fulfill this necessity NLP has been emerged as the means of interaction which narrows the gap between machines (computers) and humans. It was evolved from the study of linguistics which was passed through the Turing test to check the similarity between data but it was limited to small set of data. Later on various algorithms were developed along with the concept of AI (Artificial Intelligence) for the successful execution of NLP. In this paper, the main emphasis is on the different techniques of NLP which have been developed till now, their applications and the comparison of all those techniques on different parameters.
Embracing Social Software And Semantic Web In Digital LibrariesAkhmad Riza Faizal
1) The document discusses social software and semantic web technologies in digital libraries based on a literature review. It describes various social software tools and their usage in research libraries.
2) It also discusses recommendations and challenges regarding personalization in digital libraries, including modeling users, balancing personal and community needs, and evaluating social effects.
3) The use of open source systems like WordPress to customize digital library interfaces is presented, along with issues in managing library data and skills.
4) Examples of mobile social software and semantic digital libraries are provided, with definitions and differences between conventional and semantic digital libraries.
WP3 Further specification of Functionality and Interoperability - GradmannEuropeana
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.
Data Science Tools and Technologies: A Comprehensive Overviewsaniakhan8105
"Data Science Tools and Technologies: A Comprehensive Overview" explores the essential tools and platforms that data scientists use to analyze, visualize, and interpret complex data. From programming languages like Python and R to advanced frameworks like TensorFlow and Hadoop, this guide covers everything needed for effective data science practice.
Arabic SentiWordNet in Relation to SentiWordNet 3.0Waqas Tariq
Sentiment analysis and opinion mining are the tasks of identifying positive or negative opinions and emotions from pieces of text. The SentiWordNet (SWN) plays an important role in extracting opinions from texts. It is a publicly available sentiment measuring tool used in sentiment classification and opinion mining. We firstly discuss the development of the English SWN for versions 1.0 and 3.0. This is to provide the basis for developing an equivalent SWN for the Arabic language through a mapping to the latest version of the English SWN 3.0. We also discuss the construction of an annotated sentiment corpus for Arabic and its relationship to the Arabic SWN.
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.
A NOVEL APPROACH OF CLASSIFICATION TECHNIQUES FOR CLIRcscpconf
Recent and continuing advances in online information systems are creating many opportunities
and also new problems in information retrieval. Gathering the information in different natural
language is the most difficult task, which often requires huge resources. Cross-language
information retrieval (CLIR) is the retrieval of information for a query written in the native
language. This paper deals with various classification techniques that can be used for solving
the problems encountered in CLIR.
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Engaging Students Competition and Polls.pptxOlga Scrivner
The document discusses strategies for improving student engagement in online learning settings. It suggests that tools like polls, surveys, and competitive games through platforms like Poll Everywhere and Quizlet can enhance student connectedness and engagement. When students are more engaged through interactive activities, they exhibit stronger course achievement and higher graduation rates. The document provides an overview of Poll Everywhere and Quizlet as examples of online tools that faculty can utilize to build class unity and foster in-depth thought among students in an online environment.
HICSS ATLT: Advances in Teaching and Learning TechnologiesOlga Scrivner
The document summarizes recent research presented at the Hawaii International Conference on System Sciences related to using virtual and augmented reality technologies in education. Key points discussed include the potential of these technologies to enhance learning through immersive experiences, interaction, and customized instruction. Several studies examined how virtual reality can support different levels of learning and topics. Design principles for virtual reality learning emphasized aligning the technology with learning objectives and incorporating interactivity, motivation, and multi-sensory experiences.
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This document provides an overview of machine learning concepts including classification, regression, and clustering. It introduces Jupyter Notebook and shows how to import datasets, clean data, visualize data, train models, and evaluate predictions. Examples use the iris dataset to demonstrate classification with decision trees and k-means clustering. Requirements for linear regression are also outlined. Key Python libraries discussed include pandas, NumPy, matplotlib, and scikit-learn.
CEWIT Hand-on workshop.
Link to materials - https://languagevariationsuite.wordpress.com/2020/01/31/faculty-accelerator-crash-course-rmarkdown-with-r-introduction/amp/
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If a picture is worth a thousand words, Interactive data visualizations are w...Olga Scrivner
This document discusses how interactive data visualizations can provide actionable insights. It provides examples of visualizations created by the Cyberinfrastructure for Network Science Center that show funding, publications, and collaboration networks resulting from high-performance computing investments. These visualizations help communicate the impact and return on investment of these resources. Dynamic visualizations are also described that track workforce needs, research trends, and educational offerings over time to identify skills gaps and inform decision making.
Introduction to Interactive Shiny Web ApplicationOlga Scrivner
2 hour hands-on workshop on how to create, deploy and use Shiny in research and teaching. The materials for the workshop are https://languagevariationsuite.wordpress.com/2018/11/27/introduction-to-interactive-shiny-web-applications
Video of Workshop - https://media.dlib.indiana.edu/media_objects/rj430941s
This is workshop offered via Social Science Research Center to students and faculty to become familiar with an online collaborative writing using Latex and Overleaf.
Workshop nwav 47 - LVS - Tool for Quantitative Data AnalysisOlga Scrivner
This document provides an overview of the Language Variation Suite (LVS) toolkit. The LVS is a web application designed for sociolinguistic data analysis. It allows users to upload spreadsheet data, perform data cleaning and preprocessing, generate summary statistics and cross tabulations, create data visualizations, and conduct various statistical analyses including regression modeling, clustering, and random forests. The workshop will cover the structure and functionality of the LVS through practical examples and exercises using sample sociolinguistic datasets.
Gender Disparity in Employment and EducationOlga Scrivner
Data analysis is presented at IndyBigData Visualization Challenge 2018. Data is provided by MPH - see https://www.indybigdata.com/visualization-challenge/
CrashCourse: Python with DataCamp and Jupyter for BeginnersOlga Scrivner
Crash course for beginners is based on Python Introduction by Philip Schowenaars from DataCamp and Jupyter Introduction adapted from Adapted from Pryke, B. (2018). Jupyter Notebook for Beginners: A Tutorial. DataQuest. https://www.dataquest.io/blog/jupyter-notebook-tutorial/
Optimizing Data Analysis: Web application with ShinyOlga Scrivner
In the format of hands-on session, this workshop will introduce participants to the Language Variation Suite (LVS), a user-friendly interactive web application built in R. LVS provides access to advanced statistical methods and visualization techniques, such as mixed-effects modeling, conditional and random tree analyses, cluster analysis. These advanced methods enable researchers to handle imbalanced data, measure individual and group variation, estimate significance, and rank variables according to their significance.
Workshop files:
Categorical data csv – Use of R in New York (Labov 1966) - http://cl.indiana.edu/~obscrivn/docs/categoricaldata.csv
Continuous data csv – Intervocalic /d/ (Díaz-Campos et al. 2016) - http://cl.indiana.edu/~obscrivn/docs/continuousdata.csv
Language Variation Suite - https://languagevariationsuite.shinyapps.io/Pages/
Data Analysis and Visualization: R WorkflowOlga Scrivner
The lecture introduces to R project set-up, planning and deploying as well as to the concept of tidy data (Wickham and Grolemund, 2017).
Visual Insights Talks 2018 at
http://ivmooc.cns.iu.edu/
http://cns.iu.edu/
Reproducible visual analytics of public opioid dataOlga Scrivner
This document summarizes visualizations created to analyze public opioid data in the United States and Indiana. Visualizations show that drug deaths have increased 500% in recent years in both the US and Indiana. Higher opioid prescription rates correlate with more drug deaths in counties over time. While most Indiana counties have at least one substance abuse facility, Indiana has far fewer facilities per capita than neighboring states. Future work is planned to incorporate additional relevant data on topics like pharmacy robberies, needle exchange programs, and doctors prescribing fentanyl.
Building Effective Visualization Shiny WVFOlga Scrivner
This document provides an overview of web visualization tools and frameworks for business intelligence and data visualization. It discusses reactive web frameworks, the Shiny application framework from RStudio, and the Web Visualization Framework (WVF) developed by the Cyberinfrastructure for Network Science Center. Examples of visualizations created with Shiny and WVF are presented, including Sankey diagrams, streamgraphs, heatmaps, and network maps. The document concludes by discussing the future outlook for WVF and promoting an online course on information visualization.
Introduction of Cybersecurity with OSS at Code Europe 2024Hiroshi SHIBATA
I develop the Ruby programming language, RubyGems, and Bundler, which are package managers for Ruby. Today, I will introduce how to enhance the security of your application using open-source software (OSS) examples from Ruby and RubyGems.
The first topic is CVE (Common Vulnerabilities and Exposures). I have published CVEs many times. But what exactly is a CVE? I'll provide a basic understanding of CVEs and explain how to detect and handle vulnerabilities in OSS.
Next, let's discuss package managers. Package managers play a critical role in the OSS ecosystem. I'll explain how to manage library dependencies in your application.
I'll share insights into how the Ruby and RubyGems core team works to keep our ecosystem safe. By the end of this talk, you'll have a better understanding of how to safeguard your code.
Cosa hanno in comune un mattoncino Lego e la backdoor XZ?Speck&Tech
ABSTRACT: A prima vista, un mattoncino Lego e la backdoor XZ potrebbero avere in comune il fatto di essere entrambi blocchi di costruzione, o dipendenze di progetti creativi e software. La realtà è che un mattoncino Lego e il caso della backdoor XZ hanno molto di più di tutto ciò in comune.
Partecipate alla presentazione per immergervi in una storia di interoperabilità, standard e formati aperti, per poi discutere del ruolo importante che i contributori hanno in una comunità open source sostenibile.
BIO: Sostenitrice del software libero e dei formati standard e aperti. È stata un membro attivo dei progetti Fedora e openSUSE e ha co-fondato l'Associazione LibreItalia dove è stata coinvolta in diversi eventi, migrazioni e formazione relativi a LibreOffice. In precedenza ha lavorato a migrazioni e corsi di formazione su LibreOffice per diverse amministrazioni pubbliche e privati. Da gennaio 2020 lavora in SUSE come Software Release Engineer per Uyuni e SUSE Manager e quando non segue la sua passione per i computer e per Geeko coltiva la sua curiosità per l'astronomia (da cui deriva il suo nickname deneb_alpha).
How to Get CNIC Information System with Paksim Ga.pptxdanishmna97
Pakdata Cf is a groundbreaking system designed to streamline and facilitate access to CNIC information. This innovative platform leverages advanced technology to provide users with efficient and secure access to their CNIC details.
Your One-Stop Shop for Python Success: Top 10 US Python Development Providersakankshawande
Simplify your search for a reliable Python development partner! This list presents the top 10 trusted US providers offering comprehensive Python development services, ensuring your project's success from conception to completion.
HCL Notes und Domino Lizenzkostenreduzierung in der Welt von DLAUpanagenda
Webinar Recording: https://www.panagenda.com/webinars/hcl-notes-und-domino-lizenzkostenreduzierung-in-der-welt-von-dlau/
DLAU und die Lizenzen nach dem CCB- und CCX-Modell sind für viele in der HCL-Community seit letztem Jahr ein heißes Thema. Als Notes- oder Domino-Kunde haben Sie vielleicht mit unerwartet hohen Benutzerzahlen und Lizenzgebühren zu kämpfen. Sie fragen sich vielleicht, wie diese neue Art der Lizenzierung funktioniert und welchen Nutzen sie Ihnen bringt. Vor allem wollen Sie sicherlich Ihr Budget einhalten und Kosten sparen, wo immer möglich. Das verstehen wir und wir möchten Ihnen dabei helfen!
Wir erklären Ihnen, wie Sie häufige Konfigurationsprobleme lösen können, die dazu führen können, dass mehr Benutzer gezählt werden als nötig, und wie Sie überflüssige oder ungenutzte Konten identifizieren und entfernen können, um Geld zu sparen. Es gibt auch einige Ansätze, die zu unnötigen Ausgaben führen können, z. B. wenn ein Personendokument anstelle eines Mail-Ins für geteilte Mailboxen verwendet wird. Wir zeigen Ihnen solche Fälle und deren Lösungen. Und natürlich erklären wir Ihnen das neue Lizenzmodell.
Nehmen Sie an diesem Webinar teil, bei dem HCL-Ambassador Marc Thomas und Gastredner Franz Walder Ihnen diese neue Welt näherbringen. Es vermittelt Ihnen die Tools und das Know-how, um den Überblick zu bewahren. Sie werden in der Lage sein, Ihre Kosten durch eine optimierte Domino-Konfiguration zu reduzieren und auch in Zukunft gering zu halten.
Diese Themen werden behandelt
- Reduzierung der Lizenzkosten durch Auffinden und Beheben von Fehlkonfigurationen und überflüssigen Konten
- Wie funktionieren CCB- und CCX-Lizenzen wirklich?
- Verstehen des DLAU-Tools und wie man es am besten nutzt
- Tipps für häufige Problembereiche, wie z. B. Team-Postfächer, Funktions-/Testbenutzer usw.
- Praxisbeispiele und Best Practices zum sofortigen Umsetzen
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.
Salesforce Integration for Bonterra Impact Management (fka Social Solutions A...Jeffrey Haguewood
Sidekick Solutions uses Bonterra Impact Management (fka Social Solutions Apricot) and automation solutions to integrate data for business workflows.
We believe integration and automation are essential to user experience and the promise of efficient work through technology. Automation is the critical ingredient to realizing that full vision. We develop integration products and services for Bonterra Case Management software to support the deployment of automations for a variety of use cases.
This video focuses on integration of Salesforce with Bonterra Impact Management.
Interested in deploying an integration with Salesforce for Bonterra Impact Management? Contact us at sales@sidekicksolutionsllc.com to discuss next steps.
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.
In the rapidly evolving landscape of technologies, XML continues to play a vital role in structuring, storing, and transporting data across diverse systems. The recent advancements in artificial intelligence (AI) present new methodologies for enhancing XML development workflows, introducing efficiency, automation, and intelligent capabilities. This presentation will outline the scope and perspective of utilizing AI in XML development. The potential benefits and the possible pitfalls will be highlighted, providing a balanced view of the subject.
We will explore the capabilities of AI in understanding XML markup languages and autonomously creating structured XML content. Additionally, we will examine the capacity of AI to enrich plain text with appropriate XML markup. Practical examples and methodological guidelines will be provided to elucidate how AI can be effectively prompted to interpret and generate accurate XML markup.
Further emphasis will be placed on the role of AI in developing XSLT, or schemas such as XSD and Schematron. We will address the techniques and strategies adopted to create prompts for generating code, explaining code, or refactoring the code, and the results achieved.
The discussion will extend to how AI can be used to transform XML content. In particular, the focus will be on the use of AI XPath extension functions in XSLT, Schematron, Schematron Quick Fixes, or for XML content refactoring.
The presentation aims to deliver a comprehensive overview of AI usage in XML development, providing attendees with the necessary knowledge to make informed decisions. Whether you’re at the early stages of adopting AI or considering integrating it in advanced XML development, this presentation will cover all levels of expertise.
By highlighting the potential advantages and challenges of integrating AI with XML development tools and languages, the presentation seeks to inspire thoughtful conversation around the future of XML development. We’ll not only delve into the technical aspects of AI-powered XML development but also discuss practical implications and possible future directions.
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
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.
Taking AI to the Next Level in Manufacturing.pdfssuserfac0301
Read Taking AI to the Next Level in Manufacturing to gain insights on AI adoption in the manufacturing industry, such as:
1. How quickly AI is being implemented in manufacturing.
2. Which barriers stand in the way of AI adoption.
3. How data quality and governance form the backbone of AI.
4. Organizational processes and structures that may inhibit effective AI adoption.
6. Ideas and approaches to help build your organization's AI strategy.
Project Management Semester Long Project - Acuityjpupo2018
Acuity is an innovative learning app designed to transform the way you engage with knowledge. Powered by AI technology, Acuity takes complex topics and distills them into concise, interactive summaries that are easy to read & understand. Whether you're exploring the depths of quantum mechanics or seeking insight into historical events, Acuity provides the key information you need without the burden of lengthy texts.
UiPath Test Automation using UiPath Test Suite series, part 6DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 6. In this session, we will cover Test Automation with generative AI and Open AI.
UiPath Test Automation with generative AI and Open AI webinar offers an in-depth exploration of leveraging cutting-edge technologies for test automation within the UiPath platform. Attendees will delve into the integration of generative AI, a test automation solution, with Open AI advanced natural language processing capabilities.
Throughout the session, participants will discover how this synergy empowers testers to automate repetitive tasks, enhance testing accuracy, and expedite the software testing life cycle. Topics covered include the seamless integration process, practical use cases, and the benefits of harnessing AI-driven automation for UiPath testing initiatives. By attending this webinar, testers, and automation professionals can gain valuable insights into harnessing the power of AI to optimize their test automation workflows within the UiPath ecosystem, ultimately driving efficiency and quality in software development processes.
What will you get from this session?
1. Insights into integrating generative AI.
2. Understanding how this integration enhances test automation within the UiPath platform
3. Practical demonstrations
4. Exploration of real-world use cases illustrating the benefits of AI-driven test automation for UiPath
Topics covered:
What is generative AI
Test Automation with generative AI and Open AI.
UiPath integration with generative AI
Speaker:
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
33. Introduction
Language
Variation
Suite
Visual
Analytics for
Digital
Humanities
Interactive
Text Mining
Suite
Conclusion
References
Digital Humanity Manifesto 2.0 (2009) and Berry
(2011)
1st Wave: “The first wave of digital humanities work was
quantitative, mobilizing the search and retrieval
powers of the database, automating corpus
linguistics, stacking hypercards into critical
arrays”
2nd Wave: “The second wave is qualitative, interpretive”,
concentrating on new tools for creating and
curating digital repositories (Berry, 2011)
3rd Wave: Concentration on the computationality, search,
retrieval and analysis originated in
humanity-based work
32 / 54
54. Introduction
Language
Variation
Suite
Visual
Analytics for
Digital
Humanities
Interactive
Text Mining
Suite
Conclusion
References
References I
[1] Baayen, Harald. 2008. Analyzing linguistic data: A practical introduction to statistics. Cambridge:
Cambridge University Press
[2] Bentivoglio, Paola and Mercedes Sedano. 1993. Investigaci´on socioling¨u´ıstica: sus m´etodos aplicados a
una experiencia venezolana. Bolet´ın de Ling¨u´ıstica 8. 3-35
[3] Gries, Stefan Th. 2015. Quantitative designs and statistical techniques. In Douglas Biber Randi
Reppen (eds.), The Cambridge Handbook of English Corpus Linguistics. Cambridge: Cambridge
University Press
[4] Jockers, Matthew. 2014. Text Analysis with R for Students of Literature. Quantitative Methods in the
Humanities and Social Sciences. Springer International Publishing, Cham
[5] Labov, W. 1966. The Social Stratification of English in New York City. Washington: Center for Applied
Linguistics
[6] Moretti, Franco. 2005. Graphs, Maps, Trees: Abstract Models for a Literary History. Verso
[7] Oelke, Daniella, Dimitrios Kokkinakis, and Mats Malm. 2012. Advanced visual analytics methods for
literature analysis. Proceedings of the 6th EACL Workshop on Language Technology for Cultural
Heritage, Social 561Sciences, and Humanities, pages 3544
[8] Passarotti, Marco, Barbara McGillivray, and David Bamman. “A Treebank-based Study on Latin Word
Order.” In proceedings of 16th International Colloquium on Latin Linguistics, At Uppsala, Sweden.
2013, 340–352
[9] Schnapp, Jeffrey, and Peter Presner. 2009. Digital Humanities Manifesto 2.0.
[10] http://blog.kandu.com/post/57065268403/book-reading-gif
[11] http://cdn.business2community.com/wp-content/uploads/2014/09/archives01.jpg
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