LEADER 03412nam  2200841z- 450 
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035   $a(CKB)5400000000043401
035   $a(oapen)https://directory.doabooks.org/handle/20.500.12854/68456
035   $a(EXLCZ)995400000000043401
100   $a20202105d2021      |y             0
101 0 $aeng
135   $aurmn|---annan
181   $ctxt$2rdacontent
182   $cc$2rdamedia
183   $acr$2rdacarrier
200 10$aInformation Retrieval and Social Media Mining
210   $aBasel, Switzerland$cMDPI - Multidisciplinary Digital Publishing Institute$d2021
215   $a1 electronic resource (144 p.)
311   $a3-0365-0246-7 
311   $a3-0365-0247-5 
330   $aThis book presents diverse contributions related to some of the latest advances in the field of personalization and recommender systems, as well as social media and sentiment analysis. The work comprises several articles that address different problems in these areas by means of recent techniques such as deep learning, methods to analyze the structure and the dynamics of social networks, and modern language processing approaches for sentiment analysis, among others. The proposals included in the book are representative of some highly topical research directions and cover different application domains where they have been validated. These go from the recommendation of hotels, movies, music, documents, or pharmacy cross-selling to sentiment analysis in the field of telemedicine and opinion mining on news, also including the study of social capital on social media and dynamics aspects of the Twitter social network.
606   $aHistory of engineering & technology$2bicssc
610   $amusic recommender systems
610   $asocial influence
610   $asocial trust
610   $ahomophily
610   $acollaborative filtering
610   $astreaming services
610   $aego network
610   $aevents
610   $anetwork dynamics
610   $aTwitter
610   $ahybrid recommender systems
610   $afeedback collection
610   $adigital libraries
610   $ainformation retrieval
610   $areal-world data
610   $aopen-access
610   $asocial capital
610   $asocial media
610   $aoperationalization
610   $ameasurement
610   $ascoping review
610   $agraph convolutional neural network
610   $arecommender system
610   $across-sales
610   $apharmacy
610   $apopularity bias
610   $aopinion mining
610   $aopinion summarization
610   $atopic modeling
610   $asemantic similarity measures
610   $aword embeddings
610   $atext mining
610   $asentiment analysis
610   $aWeb-based questionnaire
610   $atelemedicine
610   $atelemonitoring
610   $atelehomecare
610   $arecommender systems
610   $autility
610   $amulti-criteria
610   $apenalty
610   $aover-expectation
610   $aunder-expectation
615  7$aHistory of engineering & technology
700   $aMoreno Garci?a$b Mari?a N$4edt$01297535
702   $aMoreno Garci?a$b Mari?a N$4oth
906   $aBOOK
912   $a9910557432203321
996   $aInformation Retrieval and Social Media Mining$93024509
997   $aUNINA