000			03354nam a22004815i 4500
001			978-3-658-01948-8
003			DE-He213
005			20200421112229.0
007			cr nn 008mamaa
008			130330s2013 gw | s |||| 0|eng d
020			_a9783658019488 _9978-3-658-01948-8
024	7		_a10.1007/978-3-658-01948-8 _2doi
050		4	_aQA76.9.D343
072		7	_aUNF _2bicssc
072		7	_aUYQE _2bicssc
072		7	_aCOM021030 _2bisacsh
082	0	4	_a006.312 _223
100	1		_aGedikli, Fatih. _eauthor.
245	1	0	_aRecommender Systems and the Social Web _h[electronic resource] : _bLeveraging Tagging Data for Recommender Systems / _cby Fatih Gedikli.
264		1	_aWiesbaden : _bSpringer Fachmedien Wiesbaden : _bImprint: Springer Vieweg, _c2013.
300			_aXI, 112 p. 29 illus., 14 illus. in color. _bonline resource.
336			_atext _btxt _2rdacontent
337			_acomputer _bc _2rdamedia
338			_aonline resource _bcr _2rdacarrier
347			_atext file _bPDF _2rda
505	0		_aRecommender Systems -- Social Tagging -- Algorithms -- Explanations.
520			_aThere is an increasing demand for recommender systems due to the information overload users are facing on the Web. The goal of a recommender system is to provide personalized recommendations of products or services to users. With the advent of the Social Web, user-generated content has enriched the social dimension of the Web. As user-provided content data also tells us something about the user, one can learn the user's individual preferences from the Social Web. This opens up completely new opportunities and challenges for recommender systems research. Fatih Gedikli deals with the question of how user-provided tagging data can be used to build better recommender systems. A tag recommender algorithm is proposed which recommends tags for users to annotate their favorite online resources. The author also proposes algorithms which exploit the user-provided tagging data and produce more accurate recommendations. On the basis of this idea, he shows how tags can be used to explain to the user the automatically generated recommendations in a clear and intuitively understandable form. With his book, Fatih Gedikli gives us an outlook on the next generation of recommendation systems in the Social Web sphere. Contents -  Recommender Systems -  Social Tagging -  Algorithms -  Explanations   Target Groups �         Researchers and students of computer science �         Computer and web programmers   The Author Dr. Fatih Gedikli is a research assistant in computer science at TU Dortmund, Germany.
650		0	_aComputer science.
650		0	_aData mining.
650		0	_aInformation storage and retrieval.
650		0	_aUser interfaces (Computer systems).
650	1	4	_aComputer Science.
650	2	4	_aData Mining and Knowledge Discovery.
650	2	4	_aInformation Storage and Retrieval.
650	2	4	_aUser Interfaces and Human Computer Interaction.
710	2		_aSpringerLink (Online service)
773	0		_tSpringer eBooks
776	0	8	_iPrinted edition: _z9783658019471
856	4	0	_uhttp://dx.doi.org/10.1007/978-3-658-01948-8
912			_aZDB-2-SCS
942			_cEBK
999			_c57883 _d57883