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) |
942 | _c14 | ||
999 |
_c296258 _d296258 |