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

出版时间：2005-8  出版社：北京燕山出版社  作者：Cheung, David 编  页数：864  

内容概要

The LNAI series reports state-of-the-art results in artificial intelligence re-search, development, and education, at a high level and in both printed andelectronic form. Enjoying tight cooperation with the R&D community, withnumerous individuals, as well as with prestigious organizations and societies,LNAI has grown into the most comprehensive artificial intelligence researchforum available.    The scope of LNAI spans the whole range of artificial intelligence and intelli-gent information processing including interdisciplinary topics in a variety ofapplication fields. The type of material published traditionally includes    proceedings (published in time for the respective conference)    post-proceedings (consisting of thoroughly revised final full papers)    research monographs (which may be based on PhD work)

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