LEADER 03722nam 22006615 450 001 9910337847903321 005 20200630112310.0 010 $a3-030-12528-9 024 7 $a10.1007/978-3-030-12528-8 035 $a(CKB)4100000008409066 035 $a(DE-He213)978-3-030-12528-8 035 $a(MiAaPQ)EBC5922888 035 $a(PPN)238493024 035 $a(EXLCZ)994100000008409066 100 $a20190608d2019 u| 0 101 0 $aeng 135 $aurnn#008mamaa 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aBroad Learning Through Fusions $eAn Application on Social Networks /$fby Jiawei Zhang, Philip S. Yu 205 $a1st ed. 2019. 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2019. 215 $a1 online resource (XV, 419 p. 104 illus., 81 illus. in color.) 311 $a3-030-12527-0 327 $a1 Broad Learning Introduction -- 2 Machine Learning Overview -- 3 Social Network Overview -- 4 Supervised Network Alignment -- 5 Unsupervised Network Alignment -- 6 Semi-supervised Network Alignment -- 7 Link Prediction -- 8 Community Detection -- 9 Information Diffusion -- 10 Viral Marketing -- 11 Network Embedding -- 12 Frontier and Future Directions -- References. 330 $aThis book offers a clear and comprehensive introduction to broad learning, one of the novel learning problems studied in data mining and machine learning. Broad learning aims at fusing multiple large-scale information sources of diverse varieties together, and carrying out synergistic data mining tasks across these fused sources in one unified analytic. This book takes online social networks as an application example to introduce the latest alignment and knowledge discovery algorithms. Besides the overview of broad learning, machine learning and social network basics, specific topics covered in this book include network alignment, link prediction, community detection, information diffusion, viral marketing, and network embedding. 606 $aData mining 606 $aArtificial intelligence 606 $aData structures (Computer science) 606 $aApplication software 606 $aMathematical statistics 606 $aData Mining and Knowledge Discovery$3https://scigraph.springernature.com/ontologies/product-market-codes/I18030 606 $aArtificial Intelligence$3https://scigraph.springernature.com/ontologies/product-market-codes/I21000 606 $aData Structures$3https://scigraph.springernature.com/ontologies/product-market-codes/I15017 606 $aInformation Systems Applications (incl. Internet)$3https://scigraph.springernature.com/ontologies/product-market-codes/I18040 606 $aProbability and Statistics in Computer Science$3https://scigraph.springernature.com/ontologies/product-market-codes/I17036 615 0$aData mining. 615 0$aArtificial intelligence. 615 0$aData structures (Computer science) 615 0$aApplication software. 615 0$aMathematical statistics. 615 14$aData Mining and Knowledge Discovery. 615 24$aArtificial Intelligence. 615 24$aData Structures. 615 24$aInformation Systems Applications (incl. Internet). 615 24$aProbability and Statistics in Computer Science. 676 $a006.312 676 $a006.312 700 $aZhang$b Jiawei$4aut$4http://id.loc.gov/vocabulary/relators/aut$01057909 702 $aYu$b Philip S$4aut$4http://id.loc.gov/vocabulary/relators/aut 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910337847903321 996 $aBroad Learning Through Fusions$92495425 997 $aUNINA