000 03078nam a22003735i 4500
001 296258
003 MX-SnUAN
005 20160429155301.0
007 cr nn 008mamaa
008 150903s2007 gw | o |||| 0|eng d
020 _a9783540378822
_99783540378822
024 7 _a10.1007/9783540378822
_2doi
035 _avtls000349396
039 9 _a201509030415
_bVLOAD
_c201405050344
_dVLOAD
_y201402071201
_zstaff
040 _aMX-SnUAN
_bspa
_cMX-SnUAN
_erda
050 4 _aQA75.5-76.95
100 1 _aLiu, Bing.
_eautor
_9331198
245 1 0 _aWeb Data Mining :
_bExploring Hyperlinks, Contents, and Usage Data /
_cby Bing Liu.
264 1 _aBerlin, Heidelberg :
_bSpringer Berlin Heidelberg,
_c2007.
300 _axx, 532 páginas 177 ilustraciones
_brecurso en línea.
336 _atexto
_btxt
_2rdacontent
337 _acomputadora
_bc
_2rdamedia
338 _arecurso en línea
_bcr
_2rdacarrier
347 _aarchivo de texto
_bPDF
_2rda
490 0 _aData-Centric Systems and Applications
500 _aSpringer eBooks
505 0 _aData Mining Foundations -- Association Rules and Sequential Patterns -- Supervised Learning -- Unsupervised Learning -- Partially Supervised Learning -- Web Mining -- Information Retrieval and Web Search -- Link Analysis -- Web Crawling -- Structured Data Extraction: Wrapper Generation -- Information Integration -- Opinion Mining -- Web Usage Mining.
520 _aWeb mining aims to discover useful information and knowledge from the Web hyperlink structure, page contents, and usage data. Although Web mining uses many conventional data mining techniques, it is not purely an application of traditional data mining due to the semistructured and unstructured nature of the Web data and its heterogeneity. It has also developed many of its own algorithms and techniques. Liu has written a comprehensive text on Web data mining. Key topics of structure mining, content mining, and usage mining are covered both in breadth and in depth. His book brings together all the essential concepts and algorithms from related areas such as data mining, machine learning, and text processing to form an authoritative and coherent text. The book offers a rich blend of theory and practice, addressing seminal research ideas, as well as examining the technology from a practical point of view. It is suitable for students, researchers and practitioners interested in Web mining both as a learning text and a reference book. Lecturers can readily use it for classes on data mining, Web mining, and Web search. Additional teaching materials such as lecture slides, datasets, and implemented algorithms are available online.
590 _aPara consulta fuera de la UANL se requiere clave de acceso remoto.
710 2 _aSpringerLink (Servicio en línea)
_9299170
776 0 8 _iEdición impresa:
_z9783540378815
856 4 0 _uhttp://remoto.dgb.uanl.mx/login?url=http://dx.doi.org/10.1007/978-3-540-37882-2
_zConectar a Springer E-Books (Para consulta externa se requiere previa autentificación en Biblioteca Digital UANL)
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999 _c296258
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