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001436957 001__ 1436957
001436957 003__ OCoLC
001436957 005__ 20230309004122.0
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001436957 007__ cr\cn\nnnunnun
001436957 008__ 210601s2021\\\\si\a\\\\ob\\\\000\0\eng\d
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001436957 020__ $$a9789811601002$$q(electronic bk.)
001436957 020__ $$a9811601003$$q(electronic bk.)
001436957 020__ $$a9789811601019$$q(print)
001436957 020__ $$a9811601011
001436957 020__ $$a9789811601026$$q(print)
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001436957 0247_ $$a10.1007/978-981-16-0100-2$$2doi
001436957 035__ $$aSP(OCoLC)1253375779
001436957 040__ $$aN$T$$beng$$erda$$epn$$cN$T$$dN$T$$dOCLCO$$dGW5XE$$dYDX$$dEBLCP$$dOCLCF$$dVT2$$dUKAHL$$dOCLCQ
001436957 049__ $$aISEA
001436957 050_4 $$aJA71.5
001436957 08204 $$a006.3/12$$223
001436957 1001_ $$aZong, Chengqing,$$eauthor.
001436957 24510 $$aText data mining /$$cChengqing Zong, Rui Xia, Jiajun Zhang.
001436957 264_1 $$aSingapore :$$bSpringer,$$c[2021]
001436957 300__ $$a1 online resource :$$billustrations (some color)
001436957 336__ $$atext$$btxt$$2rdacontent
001436957 337__ $$acomputer$$bc$$2rdamedia
001436957 338__ $$aonline resource$$bcr$$2rdacarrier
001436957 347__ $$atext file
001436957 347__ $$bPDF
001436957 504__ $$aIncludes bibliographical references.
001436957 5050_ $$aChapter 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.
001436957 506__ $$aAccess limited to authorized users.
001436957 520__ $$aThis 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.
001436957 588__ $$aOnline resource; title from PDF title page (EBSCO, viewed June 2, 2021).
001436957 650_0 $$aText data mining.
001436957 655_0 $$aElectronic books.
001436957 7001_ $$aXia, Rui,$$eauthor.
001436957 7001_ $$aZhang, Jiajun,$$eauthor.
001436957 77608 $$iPrint version:$$aZong, Chengqing.$$tText data mining.$$dSingapore : Springer, [2021]$$z9811600996$$z9789811600999$$w(OCoLC)1229142724
001436957 852__ $$bebk
001436957 85640 $$3Springer Nature$$uhttps://univsouthin.idm.oclc.org/login?url=https://link.springer.com/10.1007/978-981-16-0100-2$$zOnline Access$$91397441.1
001436957 909CO $$ooai:library.usi.edu:1436957$$pGLOBAL_SET
001436957 980__ $$aBIB
001436957 980__ $$aEBOOK
001436957 982__ $$aEbook
001436957 983__ $$aOnline
001436957 994__ $$a92$$bISE