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|a 9783540247753
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|a 10.1007/b97861
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|a COM031000
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|a 005.74
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|a Advances in Knowledge Discovery and Data Mining
|h [electronic resource] :
|b 8th Pacific-Asia Conference, PAKDD 2004, Sydney, Australia, May 26-28, 2004. Proceedings /
|c edited by Honghua Dai, Ramakrishnan Srikant, Chengqi Zhang.
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|a Berlin, Heidelberg :
|b Springer Berlin Heidelberg,
|c 2004.
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|a XIX, 716 p.
|b online resource.
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|a text
|b txt
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|a computer
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|a Lecture Notes in Computer Science,
|x 0302-9743 ;
|v 3056
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|a Invited Speeches -- Session 1A: Classification (I) -- Session 1B: Clustering (I) -- Session 1C: Association Rules (I) -- Session 2A: Novel Algorithms (I) -- Session 2B: Association (II) -- Session 2C: Classification (II) -- Session 3A: Event Mining, Anomaly Detection, and Intrusion Detection -- Session 3B: Ensemble Learning -- Session 3C: Bayesian Network and Graph Mining -- Session 3D: Text Mining (I) -- Session 4A: Clustering (II) -- Session 4B: Association (III) -- Session 4C: Novel Algorithms (II) -- Session 4D: Multimedia Mining -- Session 5A: Text Mining and Web Mining (II) -- Session 5B: Statistical Methods, Sequential Data Mining, and Time Series Mining -- Session 5C: Novel Algorithms (III) -- Session 5D: Biomedical Mining.
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|a ThePaci?c-AsiaConferenceonKnowledgeDiscoveryandDataMining(PAKDD) has been held every year since 1997. This year, the eighth in the series (PAKDD 2004) was held at Carlton Crest Hotel, Sydney, Australia, 26–28 May 2004. PAKDD is a leading international conference in the area of data mining. It p- vides an international forum for researchers and industry practitioners to share their new ideas, original research results and practical development experiences from all KDD-related areas including data mining, data warehousing, machine learning, databases, statistics, knowledge acquisition and automatic scienti?c discovery, data visualization, causal induction, and knowledge-based systems. The selection process this year was extremely competitive. We received 238 researchpapersfrom23countries,whichisthehighestinthehistoryofPAKDD, and re?ects the recognition of and interest in this conference. Each submitted research paper was reviewed by three members of the program committee. F- lowing this independent review, there were discussions among the reviewers, and when necessary, additional reviews from other experts were requested. A total of 50 papers were selected as full papers (21%), and another 31 were selected as short papers (13%), yielding a combined acceptance rate of approximately 34%. The conference accommodated both research papers presenting original - vestigation results and industrial papers reporting real data mining applications andsystemdevelopmentexperience.Theconferencealsoincludedthreetutorials on key technologies of knowledge discovery and data mining, and one workshop focusing on speci?c new challenges and emerging issues of knowledge discovery anddatamining.ThePAKDD2004programwasfurtherenhancedwithkeynote speeches by two outstanding researchers in the area of knowledge discovery and data mining: Philip Yu, Manager of Software Tools and Techniques, IBM T.J.
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|a Computer science.
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|a Data structures (Computer science).
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|a Mathematical statistics.
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|a Database management.
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|a Information storage and retrieval.
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|a Multimedia information systems.
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|a Artificial intelligence.
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|a Computer Science.
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|a Data Structures, Cryptology and Information Theory.
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|a Artificial Intelligence (incl. Robotics).
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|a Database Management.
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|a Information Storage and Retrieval.
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|a Multimedia Information Systems.
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|a Probability and Statistics in Computer Science.
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|a Dai, Honghua.
|e editor.
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|a Srikant, Ramakrishnan.
|e editor.
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|a Zhang, Chengqi.
|e editor.
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|a SpringerLink (Online service)
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|t Springer eBooks
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|i Printed edition:
|z 9783540220640
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|a Lecture Notes in Computer Science,
|x 0302-9743 ;
|v 3056
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|u http://dx.doi.org/10.1007/b97861
|z Full Text via HEAL-Link
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|a Computer Science (Springer-11645)
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