LEADER 03697nam 22006495 450 001 996203611703316 005 20220601171448.0 010 $a3-642-55192-0 024 7 $a10.1007/978-3-642-55192-5 035 $a(CKB)3710000000106796 035 $a(DE-He213)978-3-642-55192-5 035 $a(SSID)ssj0001204789 035 $a(PQKBManifestationID)11686560 035 $a(PQKBTitleCode)TC0001204789 035 $a(PQKBWorkID)11182295 035 $a(PQKB)10736639 035 $a(MiAaPQ)EBC3096952 035 $a(PPN)178320498 035 $a(EXLCZ)993710000000106796 100 $a20140430d2014 u| 0 101 0 $aeng 135 $aurnn#008mamaa 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aAgents and Data Mining Interaction$b[electronic resource] $e9th International Workshop, ADMI 2013, Saint Paul, MN, USA, May 6-7, 2013, Revised Selected Papers /$fedited by Longbing Cao, Yifeng Zeng, Andreas L. Symeonidis, Vladimir Gorodetsky, Jörg P. Müller, Philip S. Yu 205 $a1st ed. 2014. 210 1$aBerlin, Heidelberg :$cSpringer Berlin Heidelberg :$cImprint: Springer,$d2014. 215 $a1 online resource (IX, 137 p. 45 illus.) 225 1 $aLecture Notes in Artificial Intelligence ;$v8316 300 $aBibliographic Level Mode of Issuance: Monograph 311 $a3-642-55191-2 327 $aUsing Dynamic Bayesian Networks to Model User-Experience -- Multi-Agent Joint Learning from Argumentation -- Towards Mining Norms in Open Source Software Repositories -- The Recognition of Multiple Virtual Identities Association Based on Multi-Agent System -- Redundant Feature Selection for Telemetry Data -- Mining Emerging Patterns of PIU from Computer-Mediated Interaction Events -- Learning Heterogeneous Coupling Relationships between Non-IID Terms -- Learning the Hotness of Information Discussions with Multi-Dimensional Hawkes Processes -- A Spectral Clustering Algorithm Based on Hierarchical Method -- Transitive Identity Mapping using Force-Based Clustering. 330 $aThis book constitutes the thoroughly refereed and revised selected papers from the 9th International Workshop on Agents and Data Mining Interaction, ADMI 2013, held in Saint Paul, MN, USA in May 2013. The 10 papers presented in this volume were carefully selected for inclusion in the book and are organized in topical sections named agent mining and data mining. 410 0$aLecture Notes in Artificial Intelligence ;$v8316 606 $aArtificial intelligence 606 $aData mining 606 $aArtificial Intelligence$3https://scigraph.springernature.com/ontologies/product-market-codes/I21000 606 $aData Mining and Knowledge Discovery$3https://scigraph.springernature.com/ontologies/product-market-codes/I18030 615 0$aArtificial intelligence. 615 0$aData mining. 615 14$aArtificial Intelligence. 615 24$aData Mining and Knowledge Discovery. 676 $a006.3 702 $aCao$b Longbing$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aZeng$b Yifeng$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aSymeonidis$b Andreas L$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aGorodetsky$b Vladimir$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aMu?ller$b Jo?rg P.$f1965-$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aYu$b Philip S$4edt$4http://id.loc.gov/vocabulary/relators/edt 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a996203611703316 996 $aAgents and Data Mining Interaction$92829961 997 $aUNISA