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008 150923s2015 gw | s |||| 0|eng d
020 _a9783319227351
_z978-3-319-22735-1
024 7 _a10.1007/978-3-319-22735-1
_2doi
040 _aTR-AnTOB
_beng
_cTR-AnTOB
_erda
050 4 _aQA76.76.A65
072 7 _aUNH
_2bicssc
072 7 _aCOM032000
_2bisacsh
072 7 _aUNH
_2thema
072 7 _aUDBD
_2thema005.7
_223
100 1 _aSchall, Daniel.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
245 1 0 _aSocial Network-Based Recommender Systems /
_cby Daniel Schall.
250 _a1st ed. 2015.
264 1 _aCham :
_bSpringer International Publishing :
_bImprint: Springer,
_c2015.
300 _a1 online resource
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
505 0 _aOverview of Social Recommender Systems -- Link Prediction for Directed Graphs -- Follow Recommendation in Communities -- Partner Recommendation -- Social Broker Recommendation -- Conclusion.
520 _aThis book introduces novel techniques and algorithms necessary to support the formation of social networks. Concepts such as link prediction, graph patterns, recommendation systems based on user reputation, strategic partner selection, collaborative systems and network formation based on ‘social brokers’ are presented. Chapters cover a wide range of models and algorithms, including graph models and a personalized PageRank model. Extensive experiments and scenarios using real world datasets from GitHub, Facebook, Twitter, Google Plus and the European Union ICT research collaborations serve to enhance reader understanding of the material with clear applications. Each chapter concludes with an analysis and detailed summary. Social Network-Based Recommender Systems is designed as a reference for professionals and researchers working in social network analysis and companies working on recommender systems. Advanced-level students studying computer science, statistics or mathematics will also find this books useful as a secondary text.
650 0 _aSocial sciences
_xData processing.
650 1 4 _aInformation Systems Applications (incl. Internet).
_0http://scigraph.springernature.com/things/product-market-codes/I18040
650 2 4 _aGraph Theory.
_0http://scigraph.springernature.com/things/product-market-codes/M29020
650 2 4 _aComputer Appl. in Social and Behavioral Sciences.
_0http://scigraph.springernature.com/things/product-market-codes/I23028
710 2 _aSpringerLink (Online service)
856 4 0 _uhttps://doi.org/10.1007/978-3-319-22735-1
_3Springer eBooks
_zOnline access link to the resource
942 _2lcc
_cEBK
041 _aeng