Knowledge discovery in databases : PKDD 2004 : 8th European Conference on Principles and Practice of Knowledge Discovery in Databases, Pisa, Italy, September 20-24, 2004 : proceedings
著者
書誌事項
Knowledge discovery in databases : PKDD 2004 : 8th European Conference on Principles and Practice of Knowledge Discovery in Databases, Pisa, Italy, September 20-24, 2004 : proceedings
（Lecture notes in computer science, 3202 . Lecture notes in artificial intelligence）
Springer, c2004
大学図書館所蔵 全24件
内容説明・目次
内容説明
The proceedings of ECML/PKDD 2004 are published in two separate, albeit - tertwined,volumes:theProceedingsofthe 15thEuropeanConferenceonMac- ne Learning (LNAI 3201) and the Proceedings of the 8th European Conferences on Principles and Practice of Knowledge Discovery in Databases (LNAI 3202). The two conferences were co-located in Pisa, Tuscany, Italy during September 20-24, 2004. It was the fourth time in a row that ECML and PKDD were co-located. - ter the successful co-locations in Freiburg (2001), Helsinki (2002), and Cavtat- Dubrovnik (2003), it became clear that researchersstrongly supported the or- nization of a major scienti?c event about machine learning and data mining in Europe. We are happy to provide some statistics about the conferences. 581 di?erent papers were submitted to ECML/PKDD (about a 75% increase over 2003); 280 weresubmittedtoECML2004only,194weresubmittedtoPKDD2004only,and 107weresubmitted to both.Aroundhalfofthe authorsforsubmitted papersare from outside Europe, which is a clear indicator of the increasing attractiveness of ECML/PKDD. The Program Committee members were deeply involved in what turned out to be a highly competitive selection process.
We assigned each paper to 3 - viewers, deciding on the appropriate PC for papers submitted to both ECML and PKDD. As a result, ECML PC members reviewed 312 papers and PKDD PC members reviewed 269 papers. We accepted for publication regular papers (45 for ECML 2004 and 39 for PKDD 2004) and short papers that were as- ciated with poster presentations (6 for ECML 2004 and 9 for PKDD 2004). The globalacceptance ratewas14.5%for regular papers(17% if we include the short papers).
目次
Invited Papers.- Random Matrices in Data Analysis.- Data Privacy.- Breaking Through the Syntax Barrier: Searching with Entities and Relations.- Real-World Learning with Markov Logic Networks.- Strength in Diversity: The Advance of Data Analysis.- Contributed Papers.- Mining Positive and Negative Association Rules: An Approach for Confined Rules.- An Experiment on Knowledge Discovery in Chemical Databases.- Shape and Size Regularization in Expectation Maximization and Fuzzy Clustering.- Combining Multiple Clustering Systems.- Reducing Data Stream Sliding Windows by Cyclic Tree-Like Histograms.- A Framework for Data Mining Pattern Management.- Spatial Associative Classification at Different Levels of Granularity: A Probabilistic Approach.- AutoPart: Parameter-Free Graph Partitioning and Outlier Detection.- Properties and Benefits of Calibrated Classifiers.- A Tree-Based Approach to Clustering XML Documents by Structure.- Discovery of Regulatory Connections in Microarray Data.- Learning from Little: Comparison of Classifiers Given Little Training.- Geometric and Combinatorial Tiles in 0-1 Data.- Document Classification Through Interactive Supervision of Document and Term Labels.- Classifying Protein Fingerprints.- Finding Interesting Pass Patterns from Soccer Game Records.- Discovering Unexpected Information for Technology Watch.- Scalable Density-Based Distributed Clustering.- Summarization of Dynamic Content in Web Collections.- Mining Thick Skylines over Large Databases.- Ensemble Feature Ranking.- Privately Computing a Distributed k-nn Classifier.- Incremental Nonlinear PCA for Classification.- A Spectroscopy of Texts for Effective Clustering.- Constraint-Based Mining of Episode Rules and Optimal Window Sizes.- Analysing Customer Churn in Insurance Data - A Case Study.- Nomograms for Visualization of Naive Bayesian Classifier.- Using a Hash-Based Method for Apriori-Based Graph Mining.- Evaluation of Rule Interestingness Measures with a Clinical Dataset on Hepatitis.- Classification in Geographical Information Systems.- Digging into Acceptor Splice Site Prediction: An Iterative Feature Selection Approach.- Itemset Classified Clustering.- Combining Winnow and Orthogonal Sparse Bigrams for Incremental Spam Filtering.- Asynchronous and Anticipatory Filter-Stream Based Parallel Algorithm for Frequent Itemset Mining.- A Quantification of Cluster Novelty with an Application to Martian Topography.- Density-Based Spatial Clustering in the Presence of Obstacles and Facilitators.- Text Mining for Finding Functional Community of Related Genes Using TCM Knowledge.- Dealing with Predictive-but-Unpredictable Attributes in Noisy Data Sources.- A New Scheme on Privacy Preserving Association Rule Mining.- Posters.- A Unified and Flexible Framework for Comparing Simple and Complex Patterns.- Constructing (Almost) Phylogenetic Trees from Developmental Sequences Data.- Learning from Multi-source Data.- The Anatomy of SnakeT: A Hierarchical Clustering Engine for Web-Page Snippets.- COCOA: Compressed Continuity Analysis for Temporal Databases.- Discovering Interpretable Muscle Activation Patterns with the Temporal Data Mining Method.- A Tolerance Rough Set Approach to Clustering Web Search Results.- Improving the Performance of the RISE Algorithm.- Mining History of Changes to Web Access Patterns.- Demonstration Papers.- Visual Mining of Spatial Time Series Data.- Detecting Driving Awareness.- An Effective Recommender System for Highly Dynamic and Large Web Sites.- SemanticTalk: Software for Visualizing Brainstorming Sessions and Thematic Concept Trails on Document Collections.- Orange: From Experimental Machine Learning to Interactive Data Mining.- Terrorist Detection System.- Experimenting SnakeT: A Hierarchical Clustering Engine for Web-Page Snippets.- HIClass: Hyper-interactive Text Classification by Interactive Supervision of Document and Term Labels.- Balios - The Engine for Bayesian Logic Programs.- SEWeP: A Web Mining System Supporting Semantic Personalization.- SPIN! Data Mining System Based on Component Architecture.
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