Author: Professor Steven SimskePublish On: 2021-01-31
This clearly written text explains the functional applications of search, translation, optimization, and learning with regard to text analytics.
Author: Professor Steven Simske
Publisher:
ISBN: 8770223432
Category:
Page:
View: 401
Text analytics can provide a wide breadth of valuable information, including summarization, clustering, classification, and categorization to enable better functional interaction with the text. This includes improved search, translation, optimization, and learning.
Section l.1.4 Treatments of browsing germane to text mining and related applications include Chang and Rice ... a functional level, text mining systems follow the general model provided by some classic data mining applications and are ...
Author: Ronen Feldman
Publisher: Cambridge University Press
ISBN: 9780521836579
Category: Computers
Page: 410
View: 398
Text mining is a new and exciting area of computer science research that tries to solve the crisis of information overload by combining techniques from data mining, machine learning, natural language processing, information retrieval, and knowledge management. Similarly, link detection – a rapidly evolving approach to the analysis of text that shares and builds upon many of the key elements of text mining – also provides new tools for people to better leverage their burgeoning textual data resources. The Text Mining Handbook presents a comprehensive discussion of the state-of-the-art in text mining and link detection. In addition to providing an in-depth examination of core text mining and link detection algorithms and operations, the book examines advanced pre-processing techniques, knowledge representation considerations, and visualization approaches. Finally, the book explores current real-world, mission-critical applications of text mining and link detection in such varied fields as M&A business intelligence, genomics research and counter-terrorism activities.
Author: María de los Ángeles Gómez GonzálezPublish On: 2014-05-15
Machine learning algorithms have indeed proved to be extremely useful, not only in the field of sentiment analysis, but in most text mining and information retrieval applications, although their obvious disadvantage in terms of ...
Author: María de los Ángeles Gómez González
Publisher: John Benjamins Publishing Company
ISBN: 9789027270207
Category: Language Arts & Disciplines
Page: 292
View: 536
Over the last forty years, the functionalist approach to linguistic description and explanation has given rise to several major schools of thought that share two crucial assumptions: (i) form is not independent of meaning/function or language use; and (ii) linguistic description and explanation need to take into account the communicative function of language. This volume offers readers interested in functional linguistics a selected sample of studies that jointly prove the efficacy of the analytical tools and procedures broadly accepted within the functionalist tradition in order to investigate language and discourse, with special focus on key pragmatic/discourse notions such as contextualization, grammaticalisation, reference, politeness, (in-)directness, discourse markers, speech acts, subjective evaluation and sentiment analysis in texts, among others. In addition, this volume offers specific corpus-based techniques for the objective contextualisation of linguistic data, which is crucial given the central role allotted to context in both functional linguistics and pragmatics/discourse analysis.
Author: Management Association, Information ResourcesPublish On: 2016-12-12
Concepts, Methodologies, Tools, and Applications Management Association, Information Resources. • Although some text analytics systems apply exclusively advanced statistical methods, many others apply more extensive natural language ...
Author: Management Association, Information Resources
Publisher: IGI Global
ISBN: 9781522517603
Category: Computers
Page: 3048
View: 540
Ongoing advancements in modern technology have led to significant developments in artificial intelligence. With the numerous applications available, it becomes imperative to conduct research and make further progress in this field. Artificial Intelligence: Concepts, Methodologies, Tools, and Applications provides a comprehensive overview of the latest breakthroughs and recent progress in artificial intelligence. Highlighting relevant technologies, uses, and techniques across various industries and settings, this publication is a pivotal reference source for researchers, professionals, academics, upper-level students, and practitioners interested in emerging perspectives in the field of artificial intelligence.
Data, Text and Web Mining and Their Business Applications A. Zanasi C. A. Brebbia, Nelson F. F. Ebecken. 2.2 The lexical system The automatic linguistic analysis of the textual documents is based on Morphological, Syntactic, Functional ...
Author: A. Zanasi
Publisher: WIT Press
ISBN: 9781845640811
Category: Computers
Page: 346
View: 241
Information Engineering Management has found applications in many areas, including environmental conservation, economic planning, resource integration, cartography, urban planning, risk assessment, pollution control and transport management systems. Technology plays an active role in the relationship of Data Mining to environmental conservation planning.Bringing together papers presented at the Eighth International Conference on Data, Text and Web Mining and their Business Applications, this book addresses the new developments in this important field. Featured topics include: Text Mining; Web Content, Structures and Usage Mining; Clustering Technologies; Categorisation Methods; Link Analysis; Data Preparation; Applications in Business, Industry and Government; Applications in Science Engineering; National Security; Customer Relationship Management; Competitive Intelligence; Mining Environment and Geospatial Data; Business Process Management (BPM); Enterprise Information Systems; Applications of GIS and GPS; Applications of MIS; Remote Sensing; Information Systems Strategies and Methodologies and Bio Informatics.
Leverage Natural Language Processing (NLP) in Python and learn how to set up your own robust environment for performing text analytics. This second edition has gone through a major revamp and introduces several significant changes and new topics based on the recent trends in NLP. You’ll see how to use the latest state-of-the-art frameworks in NLP, coupled with machine learning and deep learning models for supervised sentiment analysis powered by Python to solve actual case studies. Start by reviewing Python for NLP fundamentals on strings and text data and move on to engineering representation methods for text data, including both traditional statistical models and newer deep learning-based embedding models. Improved techniques and new methods around parsing and processing text are discussed as well. Text summarization and topic models have been overhauled so the book showcases how to build, tune, and interpret topic models in the context of an interest dataset on NIPS conference papers. Additionally, the book covers text similarity techniques with a real-world example of movie recommenders, along with sentiment analysis using supervised and unsupervised techniques. There is also a chapter dedicated to semantic analysis where you’ll see how to build your own named entity recognition (NER) system from scratch. While the overall structure of the book remains the same, the entire code base, modules, and chapters has been updated to the latest Python 3.x release. What You'll Learn • Understand NLP and text syntax, semantics and structure• Discover text cleaning and feature engineering• Review text classification and text clustering • Assess text summarization and topic models• Study deep learning for NLP Who This Book Is For IT professionals, data analysts, developers, linguistic experts, data scientists and engineers and basically anyone with a keen interest in linguistics, analytics and generating insights from textual data.
The function of the tool was to build a contextual model of documents using the preexisting categories as “targets. ... The text mining system FACT (Finding Associations in Collections of Text) developed by Feldman ...
Author: Gary Miner
Publisher: Academic Press
ISBN: 9780123869791
Category: Mathematics
Page: 1053
View: 317
The world contains an unimaginably vast amount of digital information which is getting ever vaster ever more rapidly. This makes it possible to do many things that previously could not be done: spot business trends, prevent diseases, combat crime and so on. Managed well, the textual data can be used to unlock new sources of economic value, provide fresh insights into science and hold governments to account. As the Internet expands and our natural capacity to process the unstructured text that it contains diminishes, the value of text mining for information retrieval and search will increase dramatically. This comprehensive professional reference brings together all the information, tools and methods a professional will need to efficiently use text mining applications and statistical analysis. The Handbook of Practical Text Mining and Statistical Analysis for Non-structured Text Data Applications presents a comprehensive how- to reference that shows the user how to conduct text mining and statistically analyze results. In addition to providing an in-depth examination of core text mining and link detection tools, methods and operations, the book examines advanced preprocessing techniques, knowledge representation considerations, and visualization approaches. Finally, the book explores current real-world, mission-critical applications of text mining and link detection using real world example tutorials in such varied fields as corporate, finance, business intelligence, genomics research, and counterterrorism activities. -Extensive case studies, most in a tutorial format, allow the reader to 'click through' the example using a software program, thus learning to conduct text mining analyses in the most rapid manner of learning possible -Numerous examples, tutorials, power points and datasets available via companion website on Elsevierdirect.com -Glossary of text mining terms provided in the appendix
... because their functionality is usually integrated in larger applications with concrete use cases and established user ... several Natural Language Processing applications share, especially systems that concentrate on text analytics ...
Author: Sakae Yamamoto
Publisher: Springer
ISBN: 9783319585215
Category: Computers
Page: 654
View: 261
The two-volume set LNCS 10273 and 10274 constitutes the refereed proceedings of the thematic track on Human Interface and the Management of Information, held as part of the 19th HCI International 2017, in Vancouver, BC, Canada, in July 2017. HCII 2017 received a total of 4340 submissions, of which 1228 papers were accepted for publication after a careful reviewing process. The 102 papers presented in these volumes were organized in topical sections as follows: Part I: Visualization Methods and Tools; Information and Interaction Design; Knowledge and Service Management; Multimodal and Embodied Interaction. Part II: Information and Learning; Information in Virtual and Augmented Reality; Recommender and Decision Support Systems; Intelligent Systems; Supporting Collaboration and User Communities; Case Studies.
Neale, A. (2006) Matching corpus data and system networks: using corpora to modify and extend the system networks for ... Nord, C. (2005) Text Analysis in Translation: Theory, Methodology, and Didactic Application of a Model for ...
Author: M.A.K. Halliday
Publisher: A&C Black
ISBN: 9780826494474
Category: Language Arts & Disciplines
Page: 299
View: 674
Designed to be the essential one-volume resource for students and researchers on Systemic Functional Linguistics.
For applications to text analysis , instruments were also drawn up ( schemata of categories , SYMLOG Atlas ) and rules were formulated . ... Functional pragmatics offers two instruments for text analysis ( pattern , procedure ) .
Author: Stefan Titscher
Publisher: SAGE
ISBN: 0761964835
Category: Language Arts & Disciplines
Page: 278
View: 442
'This volume is the most comprehensive overview to date of sociologically orientated approaches to text and discourse analysis and is worth reading even for those who are interested only in purely linguistiv approaches to text and discourse. Its main merit, I think, is that it intorduces approaches which up to now have hardley been admitted into the universe of scientific discourse' - Discourse Studies Methods of Text and Discourse Analysis provides the most comprehensive overview currently available of linguistic and sociological approaches to text and discourse analysis. Among the 10 linguistic and sociological models surveyed in this book some of the more important are Grounded Theory, Content Analysis, Conversation Analysis and Critical Discourse Analysis. The book presents each approach according to a standardised format, which allows for direct systematic comparisons. The fully annotated lists of sources provide readers with an additional means of evaluation of the competing analytical methods. Interdisciplinary and international in its aims, Methods of Text and Discourse Analysis suggests the benefits both linguists and sociologists will derive from a more intimate knowledge of each others' methods and procedures.