000			03732nam a22004575i 4500
001			299372
003			MX-SnUAN
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007			cr nn 008mamaa
008			150903s2009 gw | o |||| 0|eng d
020			_a9783642018916 _99783642018916
024	7		_a10.1007/9783642018916 _2doi
035			_avtls000353197
039		9	_a201509030523 _bVLOAD _c201405060316 _dVLOAD _y201402180938 _zstaff
040			_aMX-SnUAN _bspa _cMX-SnUAN _erda
050		4	_aQ342
100	1		_aBerendt, Bettina. _eeditor. _9331984
245	1	0	_aKnowledge Discovery Enhanced with Semantic and Social Information / _cedited by Bettina Berendt, Dunja Mladeni?, Marco Gemmis, Giovanni Semeraro, Myra Spiliopoulou, Gerd Stumme, Vojt?ch Svátek, Filip Železný.
264		1	_aBerlin, Heidelberg : _bSpringer Berlin Heidelberg, _c2009.
300			_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		_aStudies in Computational Intelligence, _x1860-949X ; _v220
500			_aSpringer eBooks
505	0		_aPrior Conceptual Knowledge in Machine Learning and Knowledge Discovery -- On Ontologies as Prior Conceptual Knowledge in Inductive Logic Programming -- A Knowledge-Intensive Approach for Semi-automatic Causal Subgroup Discovery -- A Study of the SEMINTEC Approach to Frequent Pattern Mining -- Partitional Conceptual Clustering of Web Resources Annotated with Ontology Languages -- The Ex Project: Web Information Extraction Using Extraction Ontologies -- Dealing with Background Knowledge in the SEWEBAR Project -- Web Mining 2.0 -- Item Weighting Techniques for Collaborative Filtering -- Using Term-Matching Algorithms for the Annotation of Geo-services.
520			_aThis book is a showcase of recent advances in knowledge discovery enhanced with semantic and social information. It includes eight contributed chapters that grew out of two joint workshops at ECML/PKDD 2007. There is general agreement that the effectiveness of Machine Learning and Knowledge Discovery output strongly depends not only on the quality of source data and the sophistication of learning algorithms, but also on additional input provided by domain experts. There is less agreement on whether, when and how such input can and should be formalized as explicit prior knowledge. The six chapters in the first part of the book aim to investigate this aspect by addressing four different topics: inductive logic programming; the role of human users; investigations of fully automated methods for integrating background knowledge; the use of background knowledge for Web mining. The two chapters in the second part are motivated by the Web 2.0 (r)evolution and the increasingly strong role of user-generated content. The contributions emphasize the vision of the Web as a social medium for content and knowledge sharing.
590			_aPara consulta fuera de la UANL se requiere clave de acceso remoto.
700	1		_aMladeni?, Dunja. _eeditor. _9331985
700	1		_aGemmis, Marco. _eeditor. _9336254
700	1		_aSemeraro, Giovanni. _eeditor. _9331743
700	1		_aSpiliopoulou, Myra. _eeditor. _9324636
700	1		_aStumme, Gerd. _eeditor. _9318992
700	1		_aSvátek, Vojt?ch. _eeditor. _9331661
700	1		_aŽelezný, Filip. _eeditor. _9335593
710	2		_aSpringerLink (Servicio en línea) _9299170
776	0	8	_iEdición impresa: _z9783642018909
856	4	0	_uhttp://remoto.dgb.uanl.mx/login?url=http://dx.doi.org/10.1007/978-3-642-01891-6 _zConectar a Springer E-Books (Para consulta externa se requiere previa autentificación en Biblioteca Digital UANL)
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999			_c299372 _d299372