Text Data Management and Analysis A Practical Introduction to Information Retrieval and Text Mining
The growth of "big data" created unprecedented opportunities to leverage computational and statistical approaches to turn raw data into actionable knowledge that can support various application tasks. This is especially true for the optimization of decision making in virtually all applicat...
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| Main Authors: | , |
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| Format: | Book |
| Language: | English |
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New York, NY
ACM Books
2016
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| Subjects: | |
| Online Access: | Click Here to View Status and Holdings. |
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| 020 | # | # | |a 9781970001167 |q paperback |
| 020 | # | # | |a 9781970001198 |q hardcover |
| 020 | # | # | |a 9781970001174 |q ebook |
| 020 | # | # | |a 9781970001181 |q ePub |
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| 041 | 0 | # | |a eng |
| 090 | 0 | 0 | |a QA76.9.N38 |b Z435 2016 |
| 100 | 1 | # | |a ChengXiang Zhai |e author |
| 245 | 1 | 0 | |a Text Data Management and Analysis |b A Practical Introduction to Information Retrieval and Text Mining |c ChengXiang Zhai and Sean Massung |
| 264 | # | 1 | |a New York, NY |b ACM Books |c 2016 |
| 264 | # | 4 | |c ©2016 |
| 300 | # | # | |a xx, 510 pages |b illustrations (some color) |c 25 cm |
| 336 | # | # | |a text |2 rdacontent |
| 337 | # | # | |a unmediated |2 rdamedia |
| 338 | # | # | |a volume |2 rdacarrier |
| 504 | # | # | |a Includes bibliographical references (pages [477]-488) and index |
| 505 | 0 | # | |a Introduction -- Background -- Text data understanding -- MeTA: a unified toolkit for text data management and analysis -- Overview of ext data access -- Retrieval models -- Feedback -- Search engine implementation -- Search engine evaluation -- Web search -- Recommender systems -- Overview of text data analysis -- Word association mining -- Text clustering -- Text categorization -- Text summarization -- Topic analysis -- Opinion mining and sentiment analysis -- Joint analysis of text and structured data -- Toward a unified system for text management and analysis. |
| 520 | # | # | |a The growth of "big data" created unprecedented opportunities to leverage computational and statistical approaches to turn raw data into actionable knowledge that can support various application tasks. This is especially true for the optimization of decision making in virtually all application domains such as health and medicine, security and safety, learning and education, scientific discovery, and business intelligence. Just as a microscope enables us to see things in the "micro world" and a telescope allows us to see things far away, one can imagine a "big data scope" would enable us to extend our perception ability to "see" useful hidden information and knowledge buried in the data, which can help make predictions and improve the optimality of a chosen decision. This book covers general computational techniques for managing and analyzing large amounts of text data that can help users manage and make use of text data in all kinds of applications. |
| 526 | 0 | # | |a IMCXXX |b IM246 |5 IM |
| 526 | 0 | # | |a Information Storage and Retrieval Systems |b Bachelor of Information Science (Hons) Records Management |5 Faculty of Information Management |
| 650 | # | 0 | |a Data mining |
| 650 | # | 0 | |a Natural language processing (Computer science) |
| 650 | # | 0 | |a Computational linguistics |x Statistical methods |
| 650 | # | 0 | |a Natural Language Processing |
| 700 | 1 | # | |a Sean Massung |e author |
| 856 | 4 | 0 | |z Click Here to View Status and Holdings. |u https://opac.uitm.edu.my/opac/detailsPage/detailsHome.jsp?tid=975696 |
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Natural language processing and text mining