000 03113nam a22003615i 4500
001 307870
003 MX-SnUAN
005 20160429160150.0
007 cr nn 008mamaa
008 150903s2013 gw | o |||| 0|eng d
020 _a9783658019488
_99783658019488
024 7 _a10.1007/9783658019488
_2doi
035 _avtls000362428
039 9 _a201509031037
_bVLOAD
_c201405070329
_dVLOAD
_y201402211049
_zstaff
040 _aMX-SnUAN
_bspa
_cMX-SnUAN
_erda
050 4 _aQA76.9.D343
100 1 _aGedikli, Fatih.
_eautor
_9347635
245 1 0 _aRecommender Systems and the Social Web :
_bLeveraging Tagging Data for Recommender Systems /
_cby Fatih Gedikli.
264 1 _aWiesbaden :
_bSpringer Fachmedien Wiesbaden :
_bImprint: Springer Vieweg,
_c2013.
300 _axI, 112 páginas 29 ilustraciones, 14 ilustraciones en color.
_brecurso en línea.
336 _atexto
_btxt
_2rdacontent
337 _acomputadora
_bc
_2rdamedia
338 _arecurso en línea
_bcr
_2rdacarrier
347 _aarchivo de texto
_bPDF
_2rda
500 _aSpringer eBooks
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.
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:
_z9783658019471
856 4 0 _uhttp://remoto.dgb.uanl.mx/login?url=http://dx.doi.org/10.1007/978-3-658-01948-8
_zConectar a Springer E-Books (Para consulta externa se requiere previa autentificación en Biblioteca Digital UANL)
942 _c14
999 _c307870
_d307870