Mining Text Data

DOWNLOAD

Download Mining Text Data PDF/ePub or read online books in Mobi eBooks. Click Download or Read Online button to get Mining Text Data book now. This website allows unlimited access to, at the time of writing, more than 1.5 million titles, including hundreds of thousands of titles in various foreign languages. If the content not found or just blank you must refresh this page

Mining Text Data

DOWNLOAD
Author : Charu C. Aggarwal
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-02-03

Mining Text Data written by Charu C. Aggarwal and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-02-03 with Computers categories.

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.

Mining Text Data

DOWNLOAD
Author :
language : en
Publisher:
Release Date : 2012-02-04

Mining Text Data written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-02-04 with categories.

Text Mining

DOWNLOAD
Author : Sholom M. Weiss
language : en
Publisher: Springer Science & Business Media
Release Date : 2010-01-08

Text Mining written by Sholom M. Weiss and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-01-08 with Computers categories.

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.

Text Data Mining

DOWNLOAD
Author : Chengqing Zong
language : en
Publisher: Springer Nature
Release Date : 2021-05-22

Text Data Mining written by Chengqing Zong and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-05-22 with Computers categories.

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.

Practical Text Mining And Statistical Analysis For Non Structured Text Data Applications

DOWNLOAD
Author : Gary D. Miner
language : en
Publisher: Academic Press
Release Date : 2012-01-25

Practical Text Mining And Statistical Analysis For Non Structured Text Data Applications written by Gary D. Miner and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-01-25 with Mathematics categories.

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

Introduction To Text Mining

DOWNLOAD
Author : Gabe Ignatow
language : en
Publisher:
Release Date : 2017

Introduction To Text Mining written by Gabe Ignatow and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017 with categories.

Gain a foundational understanding of the analysis of textual data sets from social media sites, digital archives, and digital surveys and interviews through the study of language and social interactions in digital environments. This course is perfect for social scientists who want to gain a conceptual overview of the text mining landscape to take first steps towards working on a text mining project or collaborating with computational colleagues. By taking this course you will: Learn the foundations of Natural Language Processing (NLP) Learn how text mining tools have been used successfully by social scientists Understand basic text processing techniques Understand how to approach narrative analysis, thematic analysis, and metaphor analysis Learn about key computer science methods for text mining, such as text classification and opinion mining.

Data Mining V

DOWNLOAD
Author : A. Zanasi
language : en
Publisher: WIT Press (UK)
Release Date : 2004

Data Mining V written by A. Zanasi and has been published by WIT Press (UK) this book supported file pdf, txt, epub, kindle and other format this book has been release on 2004 with Computers categories.

Illustrating recent advances in data mining problems and encompassing both original research results and practical development experience, this work contains papers from a September 2004 conference. Contributions from academia and industry are grouped in sections on text and web mining, techniques such as clustering and categorization, applications in business, industry, and government, and applications in customer relationship management. Material presented here will be of interest to researchers and application developers working in areas such as statistics, knowledge acquisition, data analysis, IT, data visualization, and business and industry. The US office of WIT Press is Computational Mechanics. Annotation : 2004 Book News, Inc., Portland, OR (booknews.com).

Text Mining

DOWNLOAD
Author : Taeho Jo
language : en
Publisher: Springer
Release Date : 2024-12-07

Text Mining written by Taeho Jo and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-12-07 with Computers categories.

This popular book, updated as a textbook for classroom use, 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. The book features exercises and code to help readers quickly learn and apply knowledge. Presents an array of updated techniques for preprocessing texts into structured forms, geared for classroom use; Outlines concepts of text categorization and clustering, their algorithms, and implementation guides; Includes advanced topics such as text summarization, text segmentation, topic mapping, and automatic text management.

Introduction To Text Analytics

DOWNLOAD
Author : Emily Ohman
language : en
Publisher: SAGE Publications Limited
Release Date : 2024-11-01

Introduction To Text Analytics written by Emily Ohman and has been published by SAGE Publications Limited this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-11-01 with Social Science categories.

This easy-to-follow book will revolutionise how you approach text mining and data analysis as well as equipping you with the tools, and confidence, to navigate complex qualitative data. It can be challenging to effectively combine theoretical concepts with practical, real-world applications but this accessible guide provides you with a clear step-by-step approach. Written specifically for students and early career researchers this pragmatic manual will: • Contextualise your learning with real-world data and engaging case studies. • Encourage the application of your new skills with reflective questions. • Enhance your ability to be critical, and reflective, when dealing with imperfect data. Supported by practical online resources, this book is the perfect companion for those looking to gain confidence and independence whilst using transferable data skills.

Text Mining With Machine Learning

DOWNLOAD
Author : Jan Žižka
language : en
Publisher: CRC Press
Release Date : 2019-10-31

Text Mining With Machine Learning written by Jan Žižka and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-10-31 with Computers categories.

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.