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Text Mining And Its Applications
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Book Synopsis Text Mining by : Ashok N. Srivastava
Download or read book Text Mining written by Ashok N. Srivastava and published by CRC Press. This book was released on 2009-06-15 with total page 330 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Definitive Resource on Text Mining Theory and Applications from Foremost Researchers in the FieldGiving a broad perspective of the field from numerous vantage points, Text Mining: Classification, Clustering, and Applications focuses on statistical methods for text mining and analysis. It examines methods to automatically cluster and classify te
Download or read book Text Mining written by Michael W. Berry and published by John Wiley & Sons. This book was released on 2010-02-25 with total page 222 pages. Available in PDF, EPUB and Kindle. Book excerpt: Text Mining: Applications and Theory presents the state-of-the-art algorithms for text mining from both the academic and industrial perspectives. The contributors span several countries and scientific domains: universities, industrial corporations, and government laboratories, and demonstrate the use of techniques from machine learning, knowledge discovery, natural language processing and information retrieval to design computational models for automated text analysis and mining. This volume demonstrates how advancements in the fields of applied mathematics, computer science, machine learning, and natural language processing can collectively capture, classify, and interpret words and their contexts. As suggested in the preface, text mining is needed when “words are not enough.” This book: Provides state-of-the-art algorithms and techniques for critical tasks in text mining applications, such as clustering, classification, anomaly and trend detection, and stream analysis. Presents a survey of text visualization techniques and looks at the multilingual text classification problem. Discusses the issue of cybercrime associated with chatrooms. Features advances in visual analytics and machine learning along with illustrative examples. Is accompanied by a supporting website featuring datasets. Applied mathematicians, statisticians, practitioners and students in computer science, bioinformatics and engineering will find this book extremely useful.
Book Synopsis Practical Text Mining and Statistical Analysis for Non-structured Text Data Applications by : Gary Miner
Download or read book Practical Text Mining and Statistical Analysis for Non-structured Text Data Applications written by Gary Miner and published by Academic Press. This book was released on 2012-01-11 with total page 1096 pages. Available in PDF, EPUB and Kindle. Book excerpt: "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"--
Book Synopsis Mining Text Data by : Charu C. Aggarwal
Download or read book Mining Text Data written by Charu C. Aggarwal and published by Springer Science & Business Media. This book was released on 2012-02-03 with total page 527 pages. Available in PDF, EPUB and Kindle. Book excerpt: Text mining applications have experienced tremendous advances because of web 2.0 and social networking applications. Recent advances in hardware and software technology have lead to a number of unique scenarios where text mining algorithms are learned. Mining Text Data introduces an important niche in the text analytics field, and is an edited volume contributed by leading international researchers and practitioners focused on social networks & data mining. This book contains a wide swath in topics across social networks & data mining. Each chapter contains a comprehensive survey including the key research content on the topic, and the future directions of research in the field. There is a special focus on Text Embedded with Heterogeneous and Multimedia Data which makes the mining process much more challenging. A number of methods have been designed such as transfer learning and cross-lingual mining for such cases. Mining Text Data simplifies the content, so that advanced-level students, practitioners and researchers in computer science can benefit from this book. Academic and corporate libraries, as well as ACM, IEEE, and Management Science focused on information security, electronic commerce, databases, data mining, machine learning, and statistics are the primary buyers for this reference book.
Book Synopsis The Text Mining Handbook by : Ronen Feldman
Download or read book The Text Mining Handbook written by Ronen Feldman and published by Cambridge University Press. This book was released on 2007 with total page 423 pages. Available in PDF, EPUB and Kindle. Book excerpt: Publisher description
Book Synopsis Text Mining and Its Applications to Intelligence, CRM and Knowledge Management by : A. Zanasi
Download or read book Text Mining and Its Applications to Intelligence, CRM and Knowledge Management written by A. Zanasi and published by Wit Pr/Computational Mechanics. This book was released on 2005 with total page 327 pages. Available in PDF, EPUB and Kindle. Book excerpt: Primarily intended for business analysts and statisticians across multiple industries, this book provides an introduction to the types of problems encountered and current available text mining solutions.
Book Synopsis Text Mining and its Applications by : Spiros Sirmakessis
Download or read book Text Mining and its Applications written by Spiros Sirmakessis and published by Springer. This book was released on 2012-12-06 with total page 207 pages. Available in PDF, EPUB and Kindle. Book excerpt: The world of text mining is simultaneously a minefield and a gold mine. It is an exciting application field and an area of scientific research that is currently under rapid development. It uses techniques from well-established scientific fields (e.g. data mining, machine learning, information retrieval, natural language processing, case based reasoning, statistics and knowledge management) in an effort to help people gain insight, understand and interpret large quantities of (usually) semi-structured and unstructured data. Despite the advances made during the last few years, many issues remain umesolved. Proper co-ordination activities, dissemination of current trends and standardisation of the procedures have been identified, as key needs. There are many questions still unanswered, especially to the potential users; what is the scope of Text Mining, who uses it and for what purpose, what constitutes the leading trends in the field of Text Mining -especially in relation to IT- and whether there still remain areas to be covered.
Book Synopsis Emerging Technologies of Text Mining: Techniques and Applications by : do Prado, Hercules Antonio
Download or read book Emerging Technologies of Text Mining: Techniques and Applications written by do Prado, Hercules Antonio and published by IGI Global. This book was released on 2007-10-31 with total page 376 pages. Available in PDF, EPUB and Kindle. Book excerpt: "This book provides the most recent technical information related to the computational models of the text mining process, discussing techniques within the realms of classification, association analysis, information extraction, and clustering. Offering an innovative approach to the utilization of textual information mining to maximize competitive advantage, it will provide libraries with the defining reference on this topic"--Provided by publisher.
Book Synopsis Text Analytics by : John Atkinson-Abutridy
Download or read book Text Analytics written by John Atkinson-Abutridy and published by CRC Press. This book was released on 2022-05-03 with total page 201 pages. Available in PDF, EPUB and Kindle. Book excerpt: Text Analytics: An Introduction to the Science and Applications of Unstructured Information Analysis is a concise and accessible introduction to the science and applications of text analytics (or text mining), which enables automatic knowledge discovery from unstructured information sources, for both industrial and academic purposes. The book introduces the main concepts, models, and computational techniques that enable the reader to solve real decision-making problems arising from textual and/or documentary sources. Features: Easy-to-follow step-by-step concepts and methods Every chapter is introduced in a very gentle and intuitive way so students can understand the WHYs, WHAT-IFs, WHAT-IS-THIS-FORs, HOWs, etc. by themselves Practical programming exercises in Python for each chapter Includes theory and practice for every chapter, summaries, practical coding exercises for target problems, QA, and sample code and data available for download at https://www.routledge.com/Atkinson-Abutridy/p/book/9781032249797
Book Synopsis Text Mining and Analysis by : Dr. Goutam Chakraborty
Download or read book Text Mining and Analysis written by Dr. Goutam Chakraborty and published by SAS Institute. This book was released on 2014-11-22 with total page 340 pages. Available in PDF, EPUB and Kindle. Book excerpt: Big data: It's unstructured, it's coming at you fast, and there's lots of it. In fact, the majority of big data is text-oriented, thanks to the proliferation of online sources such as blogs, emails, and social media. However, having big data means little if you can't leverage it with analytics. Now you can explore the large volumes of unstructured text data that your organization has collected with Text Mining and Analysis: Practical Methods, Examples, and Case Studies Using SAS. This hands-on guide to text analytics using SAS provides detailed, step-by-step instructions and explanations on how to mine your text data for valuable insight. Through its comprehensive approach, you'll learn not just how to analyze your data, but how to collect, cleanse, organize, categorize, explore, and interpret it as well. Text Mining and Analysis also features an extensive set of case studies, so you can see examples of how the applications work with real-world data from a variety of industries. Text analytics enables you to gain insights about your customers' behaviors and sentiments. Leverage your organization's text data, and use those insights for making better business decisions with Text Mining and Analysis. This book is part of the SAS Press program.
Book Synopsis Natural Language Processing and Text Mining by : Anne Kao
Download or read book Natural Language Processing and Text Mining written by Anne Kao and published by Springer Science & Business Media. This book was released on 2007-03-06 with total page 272 pages. Available in PDF, EPUB and Kindle. Book excerpt: Natural Language Processing and Text Mining not only discusses applications of Natural Language Processing techniques to certain Text Mining tasks, but also the converse, the use of Text Mining to assist NLP. It assembles a diverse views from internationally recognized researchers and emphasizes caveats in the attempt to apply Natural Language Processing to text mining. This state-of-the-art survey is a must-have for advanced students, professionals, and researchers.
Book Synopsis Practical Text Mining and Statistical Analysis for Non-structured Text Data Applications by : Gary D. Miner
Download or read book Practical Text Mining and Statistical Analysis for Non-structured Text Data Applications written by Gary D. Miner and published by Academic Press. This book was released on 2012-01-25 with total page 1095 pages. Available in PDF, EPUB and Kindle. Book excerpt: Practical Text Mining and Statistical Analysis for Non-structured Text Data Applications brings together all the information, tools and methods a professional will need to efficiently use text mining applications and statistical analysis. Winner of a 2012 PROSE Award in Computing and Information Sciences from the Association of American Publishers, this book 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. 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. 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
Download or read book Text Mining with R written by Julia Silge and published by "O'Reilly Media, Inc.". This book was released on 2017-06-12 with total page 193 pages. Available in PDF, EPUB and Kindle. Book excerpt: Chapter 7. Case Study : Comparing Twitter Archives; Getting the Data and Distribution of Tweets; Word Frequencies; Comparing Word Usage; Changes in Word Use; Favorites and Retweets; Summary; Chapter 8. Case Study : Mining NASA Metadata; How Data Is Organized at NASA; Wrangling and Tidying the Data; Some Initial Simple Exploration; Word Co-ocurrences and Correlations; Networks of Description and Title Words; Networks of Keywords; Calculating tf-idf for the Description Fields; What Is tf-idf for the Description Field Words?; Connecting Description Fields to Keywords; Topic Modeling.
Book Synopsis Text Mining with Machine Learning by : Jan Žižka
Download or read book Text Mining with Machine Learning written by Jan Žižka and published by CRC Press. This book was released on 2019-10-31 with total page 327 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a perspective on the application of machine learning-based methods in knowledge discovery from natural languages texts. By analysing various data sets, conclusions which are not normally evident, emerge and can be used for various purposes and applications. The book provides explanations of principles of time-proven machine learning algorithms applied in text mining together with step-by-step demonstrations of how to reveal the semantic contents in real-world datasets using the popular R-language with its implemented machine learning algorithms. The book is not only aimed at IT specialists, but is meant for a wider audience that needs to process big sets of text documents and has basic knowledge of the subject, e.g. e-mail service providers, online shoppers, librarians, etc. The book starts with an introduction to text-based natural language data processing and its goals and problems. It focuses on machine learning, presenting various algorithms with their use and possibilities, and reviews the positives and negatives. Beginning with the initial data pre-processing, a reader can follow the steps provided in the R-language including the subsuming of various available plug-ins into the resulting software tool. A big advantage is that R also contains many libraries implementing machine learning algorithms, so a reader can concentrate on the principal target without the need to implement the details of the algorithms her- or himself. To make sense of the results, the book also provides explanations of the algorithms, which supports the final evaluation and interpretation of the results. The examples are demonstrated using realworld data from commonly accessible Internet sources.
Book Synopsis Clinical Text Mining by : Hercules Dalianis
Download or read book Clinical Text Mining written by Hercules Dalianis and published by Springer. This book was released on 2018-05-14 with total page 192 pages. Available in PDF, EPUB and Kindle. Book excerpt: This open access book describes the results of natural language processing and machine learning methods applied to clinical text from electronic patient records. It is divided into twelve chapters. Chapters 1-4 discuss the history and background of the original paper-based patient records, their purpose, and how they are written and structured. These initial chapters do not require any technical or medical background knowledge. The remaining eight chapters are more technical in nature and describe various medical classifications and terminologies such as ICD diagnosis codes, SNOMED CT, MeSH, UMLS, and ATC. Chapters 5-10 cover basic tools for natural language processing and information retrieval, and how to apply them to clinical text. The difference between rule-based and machine learning-based methods, as well as between supervised and unsupervised machine learning methods, are also explained. Next, ethical concerns regarding the use of sensitive patient records for research purposes are discussed, including methods for de-identifying electronic patient records and safely storing patient records. The book’s closing chapters present a number of applications in clinical text mining and summarise the lessons learned from the previous chapters. The book provides a comprehensive overview of technical issues arising in clinical text mining, and offers a valuable guide for advanced students in health informatics, computational linguistics, and information retrieval, and for researchers entering these fields.
Book Synopsis Survey of Text Mining by : Michael W. Berry
Download or read book Survey of Text Mining written by Michael W. Berry and published by Springer Science & Business Media. This book was released on 2013-03-14 with total page 251 pages. Available in PDF, EPUB and Kindle. Book excerpt: Extracting content from text continues to be an important research problem for information processing and management. Approaches to capture the semantics of text-based document collections may be based on Bayesian models, probability theory, vector space models, statistical models, or even graph theory. As the volume of digitized textual media continues to grow, so does the need for designing robust, scalable indexing and search strategies (software) to meet a variety of user needs. Knowledge extraction or creation from text requires systematic yet reliable processing that can be codified and adapted for changing needs and environments. This book will draw upon experts in both academia and industry to recommend practical approaches to the purification, indexing, and mining of textual information. It will address document identification, clustering and categorizing documents, cleaning text, and visualizing semantic models of text.
Download or read book Working with Text written by Emma Tonkin and published by Elsevier. This book was released on 2016-07-14 with total page 346 pages. Available in PDF, EPUB and Kindle. Book excerpt: What is text mining, and how can it be used? What relevance do these methods have to everyday work in information science and the digital humanities? How does one develop competences in text mining? Working with Text provides a series of cross-disciplinary perspectives on text mining and its applications. As text mining raises legal and ethical issues, the legal background of text mining and the responsibilities of the engineer are discussed in this book. Chapters provide an introduction to the use of the popular GATE text mining package with data drawn from social media, the use of text mining to support semantic search, the development of an authority system to support content tagging, and recent techniques in automatic language evaluation. Focused studies describe text mining on historical texts, automated indexing using constrained vocabularies, and the use of natural language processing to explore the climate science literature. Interviews are included that offer a glimpse into the real-life experience of working within commercial and academic text mining. Introduces text analysis and text mining tools Provides a comprehensive overview of costs and benefits Introduces the topic, making it accessible to a general audience in a variety of fields, including examples from biology, chemistry, sociology, and criminology
