Mining Text Data

Download Mining Text Data PDF Online Free

Author :
Release : 2012-02-03
Genre : Computers
Kind :
Book Rating : 235/5 ( reviews)

Mining Text Data - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Mining Text Data write by Charu C. Aggarwal. This book was released on 2012-02-03. Mining Text Data available in PDF, EPUB and Kindle. 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

Download Text Data Mining PDF Online Free

Author :
Release : 2021-05-22
Genre : Computers
Kind :
Book Rating : 003/5 ( reviews)

Text Data Mining - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Text Data Mining write by Chengqing Zong. This book was released on 2021-05-22. Text Data Mining available in PDF, EPUB and Kindle. 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

Download Text Mining with R PDF Online Free

Author :
Release : 2017-06-12
Genre : Computers
Kind :
Book Rating : 628/5 ( reviews)

Text Mining with R - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Text Mining with R write by Julia Silge. This book was released on 2017-06-12. Text Mining with R available in PDF, EPUB and Kindle. 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

Download Practical Text Mining and Statistical Analysis for Non-structured Text Data Applications PDF Online Free

Author :
Release : 2012-01-11
Genre : Computers
Kind :
Book Rating : 79X/5 ( reviews)

Practical Text Mining and Statistical Analysis for Non-structured Text Data Applications - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Practical Text Mining and Statistical Analysis for Non-structured Text Data Applications write by Gary Miner. This book was released on 2012-01-11. Practical Text Mining and Statistical Analysis for Non-structured Text Data Applications available in PDF, EPUB and Kindle. "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"--

An Introduction to Text Mining

Download An Introduction to Text Mining PDF Online Free

Author :
Release : 2017-09-22
Genre : Computers
Kind :
Book Rating : 99X/5 ( reviews)

An Introduction to Text Mining - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook An Introduction to Text Mining write by Gabe Ignatow. This book was released on 2017-09-22. An Introduction to Text Mining available in PDF, EPUB and Kindle. Students in social science courses communicate, socialize, shop, learn, and work online. When they are asked to collect data for course projects they are often drawn to social media platforms and other online sources of textual data. There are many software packages and programming languages available to help students collect data online, and there are many texts designed to help with different forms of online research, from surveys to ethnographic interviews. But there is no textbook available that teaches students how to construct a viable research project based on online sources of textual data such as newspaper archives, site user comment archives, digitized historical documents, or social media user comment archives. Gabe Ignatow and Rada F. Mihalcea's new text An Introduction to Text Mining will be a starting point for undergraduates and first-year graduate students interested in collecting and analyzing textual data from online sources, and will cover the most critical issues that students must take into consideration at all stages of their research projects, including: ethical and philosophical issues; issues related to research design; web scraping and crawling; strategic data selection; data sampling; use of specific text analysis methods; and report writing.