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020 _a9783540332077
_9978-3-540-33207-7
024 7 _a10.1007/11731139
_2doi
050 4 _aQA76.9.D35
050 4 _aQ350-390
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072 7 _aGPF
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072 7 _aCOM021000
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082 0 4 _a005.73
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245 1 0 _aAdvances in Knowledge Discovery and Data Mining
_h[electronic resource] :
_b10th Pacific-Asia Conference, PAKDD 2006, Singapore, April 9-12, 2006, Proceedings /
_cedited by Wee Keong Ng, Masaru Kitsuregawa, Jianzhong Li.
250 _a1st ed. 2006.
264 1 _aBerlin, Heidelberg :
_bSpringer Berlin Heidelberg :
_bImprint: Springer,
_c2006.
300 _aXXIV, 879 p.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aLecture Notes in Artificial Intelligence,
_x2945-9141 ;
_v3918
505 0 _aKeynote Speech -- Invited Speech -- Classification -- Ensemble Learning -- Ensemble Learning -- Support Vector Machines -- Text and Document Mining -- Web Mining -- Graph and Network Mining -- Association Rule Mining -- Bio-data Mining -- Outlier and Intrusion Detection -- Privacy -- Relational Database -- Multimedia Mining -- Stream Data Mining -- Temporal Data Mining -- Temporal Data Mining -- Innovative Applications.
520 _aThe Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD) is a leading international conference in the area of data mining and knowledge discovery. This year marks the tenth anniversary of the successful annual series of PAKDD conferences held in the Asia Pacific region. It was with pleasure that we hosted PAKDD 2006 in Singapore again, since the inaugural PAKDD conference was held in Singapore in 1997. PAKDD 2006 continues its tradition of providing an international forum for researchers and industry practitioners to share their new ideas, original research results and practical development experiences from all aspects of KDD data mining, including data cleaning, data warehousing, data mining techniques, knowledge visualization, and data mining applications. This year, we received 501 paper submissions from 38 countries and regions in Asia, Australasia, North America and Europe, of which we accepted 67 (13.4%) papers as regular papers and 33 (6.6%) papers as short papers. The distribution of the accepted papers was as follows: USA (17%), China (16%), Taiwan (10%), Australia (10%), Japan (7%), Korea (7%), Germany (6%), Canada (5%), Hong Kong (3%), Singapore (3%), New Zealand (3%), France (3%), UK (2%), and the rest from various countries in the Asia Pacific region.
650 0 _aData structures (Computer science).
650 0 _aInformation theory.
650 0 _aArtificial intelligence.
650 0 _aDatabase management.
650 0 _aInformation storage and retrieval systems.
650 0 _aComputer science
_xMathematics.
650 0 _aMathematical statistics.
650 0 _aMultimedia systems.
650 1 4 _aData Structures and Information Theory.
650 2 4 _aArtificial Intelligence.
650 2 4 _aDatabase Management.
650 2 4 _aInformation Storage and Retrieval.
650 2 4 _aProbability and Statistics in Computer Science.
650 2 4 _aMultimedia Information Systems.
700 1 _aNg, Wee Keong.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
700 1 _aKitsuregawa, Masaru.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
700 1 _aLi, Jianzhong.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
710 2 _aSpringerLink (Online service)
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9783540332060
776 0 8 _iPrinted edition:
_z9783540822196
830 0 _aLecture Notes in Artificial Intelligence,
_x2945-9141 ;
_v3918
856 4 0 _uhttps://doi.org/10.1007/11731139
912 _aZDB-2-SCS
912 _aZDB-2-SXCS
912 _aZDB-2-LNC
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