Advances in knowledge discovery and data mining : 21st Pacific-Asia Conference, PAKDD 2017, Jeju, South Korea, May 23-26, 2017 : proceedings. Part II

• 作者： Pacific-Asia Conference on Knowledge Discovery and Data Mining (21st : 2017 : Cheju Island, Korea)
• 其他作者：
  • Kim, Jinho, editor.
  • Shim, Kyuseok, editor.
  • Cao, Longbing, editor.
  • Lee, Jae-Gil, editor.
  • Lin, Xuemin, editor.
  • Moon, Yang-Sae, editor.
  • SpringerLink (Online service)
• 其他題名：
  • PAKDD 2017
  • Lecture notes in computer science ;
• 出版： Cham : Springer International Publishing :Imprint: Springer
• 叢書名： Lecture notes in computer science,10235
• 主題： Data mining--Congresses. , Computer Science. , Data Mining and Knowledge Discovery. , Artificial Intelligence (incl. Robotics) , Information Storage and Retrieval. , Information Systems Applications (incl. Internet) , Database Management. , Systems and Data Security.
• ISBN： 9783319575292 (electronic bk.) 、 9783319575285 (paper)
• FIND@SFXID: CGU
• 資料類型: 電子書
• 內容註: Classification and deep learning -- Social network and graph mining -- Privacy-preserving mining and security/risk applications -- Spatio-temporal and sequential data mining -- Clustering and anomaly detection -- Recommender system -- Feature selection -- Text and opinion mining -- Clustering and matrix factorization -- Dynamic, stream data mining -- Novel models and algorithms -- Behavioral data mining -- Graph clustering and community detection -- Dimensionality reduction.
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• 摘要註: This two-volume set, LNAI 10234 and 10235, constitutes the thoroughly refereed proceedings of the 21st Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining, PAKDD 2017, held in Jeju, South Korea, in May 2017. The 129 full papers were carefully reviewed and selected from 458 submissions. They are organized in topical sections named: classification and deep learning; social network and graph mining; privacy-preserving mining and security/risk applications; spatio-temporal and sequential data mining; clustering and anomaly detection; recommender system; feature selection; text and opinion mining; clustering and matrix factorization; dynamic, stream data mining; novel models and algorithms; behavioral data mining; graph clustering and community detection; dimensionality reduction.
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