Text Data Mining

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Mining Text Data

Charu C. Aggarwal,ChengXiang Zhai
Mining Text Data Book PDF

Author : Charu C. Aggarwal,ChengXiang Zhai
Publisher : Springer Science & Business Media
Page : 524 pages
File Size : 42,8 Mb
Release : 2012-02-03
Category : Computers
ISBN : 9781461432234

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Mining Text Data by Charu C. Aggarwal,ChengXiang Zhai Pdf

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.

Text Data Mining

Chengqing Zong,Rui Xia,Jiajun Zhang
Text Data Mining Book PDF

Author : Chengqing Zong,Rui Xia,Jiajun Zhang
Publisher : Springer Nature
Page : 363 pages
File Size : 44,5 Mb
Release : 2021-05-22
Category : Computers
ISBN : 9789811601002

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Text Data Mining by Chengqing Zong,Rui Xia,Jiajun Zhang Pdf

This book discusses various aspects of text data mining. Unlike other books that focus on machine learning or databases, it approaches text data mining from a natural language processing (NLP) perspective. The book offers a detailed introduction to the fundamental theories and methods of text data mining, ranging from pre-processing (for both Chinese and English texts), text representation and feature selection, to text classification and text clustering. It also presents the predominant applications of text data mining, for example, topic modeling, sentiment analysis and opinion mining, topic detection and tracking, information extraction, and automatic text summarization. Bringing all the related concepts and algorithms together, it offers a comprehensive, authoritative and coherent overview. Written by three leading experts, it is valuable both as a textbook and as a reference resource for students, researchers and practitioners interested in text data mining. It can also be used for classes on text data mining or NLP.

Text Mining with R

Julia Silge,David Robinson
Text Mining with R Book PDF

Author : Julia Silge,David Robinson
Publisher : "O'Reilly Media, Inc."
Page : 193 pages
File Size : 43,7 Mb
Release : 2017-06-12
Category : Computers
ISBN : 9781491981627

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Text Mining with R by Julia Silge,David Robinson Pdf

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.

Practical Text Mining and Statistical Analysis for Non-structured Text Data Applications

Gary Miner
Practical Text Mining and Statistical Analysis for Non structured Text Data Applications Book PDF

Author : Gary Miner
Publisher : Academic Press
Page : 1096 pages
File Size : 52,9 Mb
Release : 2012-01-11
Category : Computers
ISBN : 9780123869791

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Practical Text Mining and Statistical Analysis for Non-structured Text Data Applications by Gary Miner Pdf

"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"--

Text Mining

Taeho Jo
Text Mining Book PDF

Author : Taeho Jo
Publisher : Springer
Page : 373 pages
File Size : 43,8 Mb
Release : 2018-06-07
Category : Technology & Engineering
ISBN : 9783319918150

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Text Mining by Taeho Jo Pdf

This book discusses text mining and different ways this type of data mining can be used to find implicit knowledge from text collections. The author provides the guidelines for implementing text mining systems in Java, as well as concepts and approaches. The book starts by providing detailed text preprocessing techniques and then goes on to provide concepts, the techniques, the implementation, and the evaluation of text categorization. It then goes into more advanced topics including text summarization, text segmentation, topic mapping, and automatic text management.

Text Mining

Ashok N. Srivastava,Mehran Sahami
Text Mining Book PDF

Author : Ashok N. Srivastava,Mehran Sahami
Publisher : CRC Press
Page : 330 pages
File Size : 47,8 Mb
Release : 2009-06-15
Category : Business & Economics
ISBN : 9781420059458

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Text Mining by Ashok N. Srivastava,Mehran Sahami Pdf

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

An Introduction to Text Mining

Gabe Ignatow,Rada Mihalcea
An Introduction to Text Mining Book PDF

Author : Gabe Ignatow,Rada Mihalcea
Publisher : SAGE Publications
Page : 344 pages
File Size : 46,5 Mb
Release : 2017-09-22
Category : Social Science
ISBN : 9781506337029

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An Introduction to Text Mining by Gabe Ignatow,Rada Mihalcea Pdf

This is the ideal introduction for students seeking to collect and analyze textual data from online sources. It covers the most critical issues that they must take into consideration at all stages of their research projects.

The Text Mining Handbook

Ronen Feldman,James Sanger
The Text Mining Handbook Book PDF

Author : Ronen Feldman,James Sanger
Publisher : Cambridge University Press
Page : 423 pages
File Size : 49,7 Mb
Release : 2007
Category : Computers
ISBN : 9780521836579

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The Text Mining Handbook by Ronen Feldman,James Sanger Pdf

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Text Data Management and Analysis

ChengXiang Zhai,Sean Massung
Text Data Management and Analysis Book PDF

Author : ChengXiang Zhai,Sean Massung
Publisher : Morgan & Claypool
Page : 530 pages
File Size : 50,7 Mb
Release : 2016-06-30
Category : Computers
ISBN : 9781970001181

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Text Data Management and Analysis by ChengXiang Zhai,Sean Massung Pdf

Recent years have seen a dramatic growth of natural language text data, including web pages, news articles, scientific literature, emails, enterprise documents, and social media such as blog articles, forum posts, product reviews, and tweets. This has led to an increasing demand for powerful software tools to help people analyze and manage vast amounts of text data effectively and efficiently. Unlike data generated by a computer system or sensors, text data are usually generated directly by humans, and are accompanied by semantically rich content. As such, text data are especially valuable for discovering knowledge about human opinions and preferences, in addition to many other kinds of knowledge that we encode in text. In contrast to structured data, which conform to well-defined schemas (thus are relatively easy for computers to handle), text has less explicit structure, requiring computer processing toward understanding of the content encoded in text. The current technology of natural language processing has not yet reached a point to enable a computer to precisely understand natural language text, but a wide range of statistical and heuristic approaches to analysis and management of text data have been developed over the past few decades. They are usually very robust and can be applied to analyze and manage text data in any natural language, and about any topic. This book provides a systematic introduction to all these approaches, with an emphasis on covering the most useful knowledge and skills required to build a variety of practically useful text information systems. The focus is on text mining applications that can help users analyze patterns in text data to extract and reveal useful knowledge. Information retrieval systems, including search engines and recommender systems, are also covered as supporting technology for text mining applications. The book covers the major concepts, techniques, and ideas in text data mining and information retrieval from a practical viewpoint, and includes many hands-on exercises designed with a companion software toolkit (i.e., MeTA) to help readers learn how to apply techniques of text mining and information retrieval to real-world text data and how to experiment with and improve some of the algorithms for interesting application tasks. The book can be used as a textbook for a computer science undergraduate course or a reference book for practitioners working on relevant problems in analyzing and managing text data.

Survey of Text Mining

Michael W. Berry
Survey of Text Mining Book PDF

Author : Michael W. Berry
Publisher : Springer Science & Business Media
Page : 251 pages
File Size : 46,5 Mb
Release : 2013-03-14
Category : Computers
ISBN : 9781475743050

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Survey of Text Mining by Michael W. Berry Pdf

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.

Clinical Text Mining

Hercules Dalianis
Clinical Text Mining Book PDF

Author : Hercules Dalianis
Publisher : Springer
Page : 192 pages
File Size : 50,8 Mb
Release : 2018-05-14
Category : Computers
ISBN : 9783319785035

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Clinical Text Mining by Hercules Dalianis Pdf

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.

Text Mining

Gabe Ignatow,Rada Mihalcea
Text Mining Book PDF

Author : Gabe Ignatow,Rada Mihalcea
Publisher : SAGE Publications
Page : 189 pages
File Size : 54,5 Mb
Release : 2016-04-20
Category : Social Science
ISBN : 9781483369327

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Text Mining by Gabe Ignatow,Rada Mihalcea Pdf

Online communities generate massive volumes of natural language data and the social sciences continue to learn how to best make use of this new information and the technology available for analyzing it. Text Mining brings together a broad range of contemporary qualitative and quantitative methods to provide strategic and practical guidance on analyzing large text collections. This accessible book, written by a sociologist and a computer scientist, surveys the fast-changing landscape of data sources, programming languages, software packages, and methods of analysis available today. Suitable for novice and experienced researchers alike, the book will help readers use text mining techniques more efficiently and productively.

Text Mining

Michael W. Berry,Jacob Kogan
Text Mining Book PDF

Author : Michael W. Berry,Jacob Kogan
Publisher : John Wiley & Sons
Page : 229 pages
File Size : 42,7 Mb
Release : 2010-05-03
Category : Mathematics
ISBN : 9780470749821

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Text Mining by Michael W. Berry,Jacob Kogan Pdf

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.

Practical Text Mining and Statistical Analysis for Non-structured Text Data Applications

Gary Miner,John Elder IV,Andrew Fast,Thomas Hill,Robert Nisbet,Dursun Delen
Practical Text Mining and Statistical Analysis for Non structured Text Data Applications Book PDF

Author : Gary Miner,John Elder IV,Andrew Fast,Thomas Hill,Robert Nisbet,Dursun Delen
Publisher : Academic Press
Page : 1000 pages
File Size : 52,7 Mb
Release : 2012-01-25
Category : Mathematics
ISBN : 9780123870117

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Practical Text Mining and Statistical Analysis for Non-structured Text Data Applications by Gary Miner,John Elder IV,Andrew Fast,Thomas Hill,Robert Nisbet,Dursun Delen Pdf

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

Text Mining

Sholom M. Weiss,Nitin Indurkhya,Tong Zhang,Fred Damerau
Text Mining Book PDF

Author : Sholom M. Weiss,Nitin Indurkhya,Tong Zhang,Fred Damerau
Publisher : Springer Science & Business Media
Page : 237 pages
File Size : 42,8 Mb
Release : 2010-01-08
Category : Computers
ISBN : 9780387345550

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Text Mining by Sholom M. Weiss,Nitin Indurkhya,Tong Zhang,Fred Damerau Pdf

Data mining is a mature technology. The prediction problem, looking for predictive patterns in data, has been widely studied. Strong me- ods are available to the practitioner. These methods process structured numerical information, where uniform measurements are taken over a sample of data. Text is often described as unstructured information. So, it would seem, text and numerical data are different, requiring different methods. Or are they? In our view, a prediction problem can be solved by the same methods, whether the data are structured - merical measurements or unstructured text. Text and documents can be transformed into measured values, such as the presence or absence of words, and the same methods that have proven successful for pred- tive data mining can be applied to text. Yet, there are key differences. Evaluation techniques must be adapted to the chronological order of publication and to alternative measures of error. Because the data are documents, more specialized analytical methods may be preferred for text. Moreover, the methods must be modi?ed to accommodate very high dimensions: tens of thousands of words and documents. Still, the central themes are similar.