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dc.contributor.editorMoreno García, María N.
dc.date.accessioned2021-05-01T15:10:32Z
dc.date.available2021-05-01T15:10:32Z
dc.date.issued2021
dc.identifierONIX_20210501_9783036502465_202
dc.identifier.urihttps://directory.doabooks.org/handle/20.500.12854/68456
dc.description.abstractThis 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.
dc.languageEnglish
dc.subject.classificationthema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technologyen_US
dc.subject.othermusic recommender systems
dc.subject.othersocial influence
dc.subject.othersocial trust
dc.subject.otherhomophily
dc.subject.othercollaborative filtering
dc.subject.otherstreaming services
dc.subject.otherego network
dc.subject.otherevents
dc.subject.othernetwork dynamics
dc.subject.otherTwitter
dc.subject.otherhybrid recommender systems
dc.subject.otherfeedback collection
dc.subject.otherdigital libraries
dc.subject.otherinformation retrieval
dc.subject.otherreal-world data
dc.subject.otheropen-access
dc.subject.othersocial capital
dc.subject.othersocial media
dc.subject.otheroperationalization
dc.subject.othermeasurement
dc.subject.otherscoping review
dc.subject.othergraph convolutional neural network
dc.subject.otherrecommender system
dc.subject.othercross-sales
dc.subject.otherpharmacy
dc.subject.otherpopularity bias
dc.subject.otheropinion mining
dc.subject.otheropinion summarization
dc.subject.othertopic modeling
dc.subject.othersemantic similarity measures
dc.subject.otherword embeddings
dc.subject.othertext mining
dc.subject.othersentiment analysis
dc.subject.otherWeb-based questionnaire
dc.subject.othertelemedicine
dc.subject.othertelemonitoring
dc.subject.othertelehomecare
dc.subject.otherrecommender systems
dc.subject.otherutility
dc.subject.othermulti-criteria
dc.subject.otherpenalty
dc.subject.otherover-expectation
dc.subject.otherunder-expectation
dc.subject.othern/a
dc.titleInformation Retrieval and Social Media Mining
dc.typebook
oapen.identifier.doi10.3390/books978-3-0365-0247-2
oapen.relation.isPublishedBy46cabcaa-dd94-4bfe-87b4-55023c1b36d0
oapen.relation.isbn9783036502465
oapen.relation.isbn9783036502472
oapen.pages144
oapen.place.publicationBasel, Switzerland


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