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210601s2021 si a ob 000 0 eng d |
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|a 9789811601002
|q (electronic bk.)
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|a 9811601003
|q (electronic bk.)
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|a 9789811601019
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|a 9811601011
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|z 9789811600999
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|z 9811600996
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|a 10.1007/978-981-16-0100-2
|2 doi
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|a (OCoLC)1253375779
|z (OCoLC)1253132713
|z (OCoLC)1262687734
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|a HCDD
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1 |
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|a Zong, Chengqing,
|e author.
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1 |
0 |
|a Text data mining /
|c Chengqing Zong, Rui Xia, Jiajun Zhang.
|
264 |
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1 |
|a Singapore :
|b Springer,
|c [2021]
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300 |
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|a 1 online resource :
|b illustrations (some color)
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|a text
|b txt
|2 rdacontent
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|a computer
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|a text file
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|b PDF
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|a Includes bibliographical references.
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|a 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.
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|a Chapter 1. Introduction -- Chapter 2. Data Annotation and Preprocessing -- Chapter 3. Text Representation -- Chapter 4. Text Representation with Pretraining and Fine-tuning -- Chapter 5. Text classification -- Chapter 6. Text Clustering -- Chapter 7. Topic Model -- Chapter 8. Sentiment Analysis and Opinion Mining -- Chapter 9. Topic Detection and Tracking -- Chapter 10. Information Extraction -- Chapter 11. Automatic Text Summarization.
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|a Online resource; title from PDF title page (EBSCO, viewed June 2, 2021).
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650 |
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|a Text data mining.
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650 |
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7 |
|a Text data mining
|2 fast
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700 |
1 |
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|a Xia, Rui,
|e author.
|
700 |
1 |
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|a Zhang, Jiajun,
|e author.
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758 |
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|i has work:
|a Text data mining (Text)
|1 https://id.oclc.org/worldcat/entity/E39PCGqwm4YBbV3dtbDFfyXTVy
|4 https://id.oclc.org/worldcat/ontology/hasWork
|
776 |
0 |
8 |
|i Print version:
|a Zong, Chengqing.
|t Text data mining.
|d Singapore : Springer, [2021]
|z 9811600996
|z 9789811600999
|w (OCoLC)1229142724
|
856 |
4 |
0 |
|u https://holycross.idm.oclc.org/login?auth=cas&url=https://link.springer.com/10.1007/978-981-16-0100-2
|y Click for online access
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903 |
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|a SPRING-COMP2021
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994 |
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|a 92
|b HCD
|