高級(jí)數(shù)據(jù)挖掘及應(yīng)用Advanced Data Mining and Applications

內(nèi)容概要

This book constitutes the refereed proceedings of the Second International Conference on Advanced Data Mining and Applications, ADMA 2006, held in Xi'an, China in August 2006.    The 41 revised full papers and 74 revised short papers presented together with 4 invited papers were carefully reviewed and selected from 515 submissions. The papers are organized in topical sections on association rules, classification, clustering, novel algorithms, text mining, multimedia mining, sequential data mining and time series mining, web mining, biomedical mining, advanced applications, security and privacy issues, spatial data mining, and streaming data mining.

書籍目錄

Invited Papers  Warehousing and Mining Massive RFID Data Sets  Self-organising Map Techniques for Graph Data Applications to Clustering of XML Documents  Finding Time Series Discords Based on Haar Transform  Learning with Local Drift DetectionAssociation Rules  A Fast Algorithm for Maintenance of Association Rules in Incremental Databases  Extending OLAP with Fuzziness for Effective Mining of Fuzzy Multidimensional Weighted Association Rules  Incremental Maintenance of Association Rules Based on Multiple Previously Mined Results  Mining and Validation of Localized Frequent Web Access Patterns with Dynamic Tolerance  SA-IFIM: Incrementally Mining Frequent Itemsets in Update Distorted Databases  Study of Positive and Negative Association Rules Based on Multi-confidence and Chi-Squared Test  Efficiently Mining Maximal Frequent Mutually Associated Patterns  Efficiently Mining Mutually and Positively Correlated PatternsClassification  ComEnVprs: A Novel Approach for Inducing Decision Tree Classifiers  Towards a Rough Classification of Business Travelers  Feature Extraction Based on Optimal Discrimination Plane in ECC Signal Classification  Music Style Classification with a Novel Bayesian Model  Classification of Polarimetric SAR Data Based on Multidimensional Watershed Clustering  An Effective Combination Based on Class-Wise Expertise of Diverse Classifiers for Predictive Toxicology Data Mining  Robust Collective Classification with Contextual Dependency Network Models  User-Centered Image Semantics Classification  A Performance Study of Gaussian Kernel Classifiers for Data Mining Applications  ……ClusteringNovel AlgorithmsText MiningMultimedia MiningSequential Data Mining and Time Series MiningWeb MiningBiomedical MiningAdvanced ApplicationsSecurity and Privacy IssuesSpatial Data MiningStreaming Data MiningAuthor Index

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