Advances in Knowledge Discovery and Data Mining知识发现与数据挖掘进展/会议录

作者简介

This book constitutes the refereed proceedings of the 9th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2005, held in Hanoi, Vietnam, in May 2005. The 48 revised full papers and 49 revised short papers presented together with abstracts or extended abstracts of 3 invited talks were carefully reviewed and selected from 327 submissions. The papers are organized in topical sections on theoretical foundations, association rules, biomedical domains, classification and ranking, clustering, dynamic data mining, graphical model discovery, high dimensional data, integration of data warehousing, knowledge management, machine learning, novel algorithms, spatial data, temporal data, and text and Web data mining.

书籍目录

Keynote Speech and Invited Talks  Machine Learning for Analyzing Human Brain Function  Subgroup Discovery Techniques and Applications  IT Development in the 21 st Century and Its ImplicationsTheoretic Foundations  Data Mining of Gene Expression Microarray via Weighted Prefix Trees  Automatic Extraction of Low Frequency Bilingual Word Paris from Parallel Corpora with Various Languages  A Kennel Function Method in Clustering  Performance Measurements for Privacy Preserving Data Mining  Extraction of Frequent Few-Overlapped Monotone DNF Formulas with Depth-First Pruning  Association Rules  Rule Extraction from Trained Support Vector Machines  Pruning Derivative Partial Rules During Impact Rule Discovery  IGB: A New Informative Generic Base of Association Rules  A Divide and Conquer Approach for Deriving Partially Ordered Sub-structures  Finding Sporadic Rules Using Apriori-Inverse  Automatic View Selection: An Application to Image Mining  Pushing Tougher Constraints in Frequent Pattern Mining  An Efficient Compression Technique for Frequent Itemset Generation in Association Rule Mining  Mining Time-Profiled Associations: An Extended Abstact  Online Algorithms for Mining Inter-stream Associations from Large Sensor Neworks  Mining Frequent Ordered PatternsBiomedical Domains  Conditional Random Fields for Transmembrane Helix Prediction  Bret Church  A DNA Index Structure Using Frequency and Position Information of Genetic Alphabet  Woo-Cheol Kim, Sanghyun Park, Jung-Im Won, Sang-Wook Kim,  An Automatic Unsupervised Querying Algorithm for Efficient Information Extraction in Biomedical Domain  Voting Fuzzy k-NN to Predict Protein Subcellular Localization fromNormalized Amino Acid Pair Compositions  Comparison of Tree Based Methods on Mammography Data Richard De Veaux, Thu Hoamg  ……Classification and RankingChssteringHigh Dimensiornal DataIntegration of Davt WarebousingKnowledge ManagementTmachint Learning MethodsNovel AlgorithonsSpatial DatasText and Web Data MiningAuthor Index

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