000			02969nam a22004335i 4500
001			u375422
003			SIRSI
005			20160812084323.0
007			cr nn 008mamaa
008			101118s2011 gw | s |||| 0|eng d
020			_a9783642168987 _9978-3-642-16898-7
040			_cMX-MeUAM
050		4	_aQ342
082	0	4	_a006.3 _223
100	1		_aRendle, Steffen. _eauthor.
245	1	0	_aContext-Aware Ranking with Factorization Models _h[recurso electrónico] / _cby Steffen Rendle.
264		1	_aBerlin, Heidelberg : _bSpringer Berlin Heidelberg, _c2011.
300			_aXII, 180 p. _bonline resource.
336			_atext _btxt _2rdacontent
337			_acomputer _bc _2rdamedia
338			_aonline resource _bcr _2rdacarrier
347			_atext file _bPDF _2rda
490	1		_aStudies in Computational Intelligence, _x1860-949X ; _v330
505	0		_aPart I Overview -- Part II Theory -- Part III Application -- Part IV Extensions -- Part V Conclusion.
520			_aContext-aware ranking is an important task with many applications. E.g. in recommender systems items (products, movies, ...) and for search engines webpages should be ranked. In all these applications, the ranking is not global (i.e. always the same) but depends on the context. Simple examples for context are the user for recommender systems and the query for search engines. More complicated context includes time, last actions, etc. The major problem is that typically the variable domains (e.g. customers, products) are categorical and huge, the observations are very sparse and only positive events are observed. In this book, a generic method for context-aware ranking as well as its application are presented. For modelling a new factorization based on pairwise interactions is proposed and compared to other tensor factorization approaches. For learning, the `Bayesian Context-aware Ranking' framework consisting of an optimization criterion and algorithm is developed. The second main part of the book applies this general theory to the three scenarios of item, tag and sequential-set recommendation. Furthermore extensions of time-variant factors and one-class problems are studied. This book generalizes and builds on work that has received the `WWW 2010 Best Paper Award', the `WSDM 2010 Best Student Paper Award' and the `ECML/PKDD 2009 Best Discovery Challenge Award'.
650		0	_aEngineering.
650		0	_aArtificial intelligence.
650	1	4	_aEngineering.
650	2	4	_aComputational Intelligence.
650	2	4	_aArtificial Intelligence (incl. Robotics).
710	2		_aSpringerLink (Online service)
773	0		_tSpringer eBooks
776	0	8	_iPrinted edition: _z9783642168970
830		0	_aStudies in Computational Intelligence, _x1860-949X ; _v330
856	4	0	_zLibro electrónico _uhttp://148.231.10.114:2048/login?url=http://link.springer.com/book/10.1007/978-3-642-16898-7
596			_a19
942			_cLIBRO_ELEC
999			_c203302 _d203302