Foundations of Intelligent Systems : 15th International Symposium, ISMIS 2005, Saratoga Springs, NY, USA, May 25-28, 2005, Proceedings (Lecture Notes

This volume contains the papers selected for presentation at the 15th International S- posiumonMethodologiesforIntelligentSystems,ISMIS2005,heldinSaratogaSprings, NewYork,25 28May,2005. ThesymposiumwasorganizedbySUNYatAlbany. Itwas sponsored by the Army Research Of?ce and by several units of the University at Albany including its Division for Research, College of Arts and Sciences, Department of C- puter Science, and Institute for Informatics, Logics, and Security Studies (formerly the Institute for Programming and Logics). ISMIS is a conference series that was started in 1986 in Knoxville, Tennessee. Since then it has been held in Charlotte (North Carolina), Knoxville(Tennessee),Turin(Italy),Trondheim(Norway),Warsaw(Poland),Zakopane (Poland), Lyon (France), and Maebashi City (Japan). The Program Committee selected the following major areas for ISMIS 2005: intelligent information systems, knowledge discovery and data mining, knowledge - formation and integration, knowledge representation, logic for arti?cial intelligence, soft computing, Web intelligence, Web services, and papers dealing with applications of intelligent systems in complex/novel domains. The contributed papers were selected from almost 200 full draft papers by the Program Committee members: Troels Andreasen, Peter Baumgartner, Boualemn Benatallah, Salima Benbernou, Veronique Benzaken, Petr Berka, Elisa Bertino, Alan Biermann, Jacques Calmet, Sandra Carberry, Juan Carlos Cubero, Luigia Carlucci Aiello, Shu-Ching Chen, Christine Collet, Agnieszka Dardzinska, Ian Davidson, Robert Demolombe, Jitender Deogun, Jon Doyle, Tapio Elomaa, Attilio Giordana, Jerzy Grzymala-Busse,MirsadHadzikadic,ReinerHaehnle,JanuszKacprzyk,VipulKashyap, Jan Komorowski, Jacek Koronacki, Tsau Young Lin, Donato Malerba, David Maluf, Davide Martinenghi, Stan Matwin, Natasha Noy, Werner Nutt, James Peters, Jean-Marc Petit, Vijay Raghavan, Jan Rauch, Gilbert Ritschard, Erik Rosenthal, Marie-Christine Rousset, Nahid Shahmehri, Andrzej Skowron, Dominik Slezak, Nicolas Spyratos, V. S. Invited Papers.- Methodologies for Automated Telephone Answering.- Anomaly Detection in Computer Security and an Application to File System Accesses.- Regular Papers.- A Machine Text-Inspired Machine Learning Approach for Identification of Transmembrane Helix Boundaries.- Visualization of Similarities and Dissimilarities in Rules Using Multidimensional Scaling.- Learning Profiles Based on Hierarchical Hidden Markov Model.- Statistical Independence from the Viewpoint of Linear Algebra.- Bitmap Index-Based Decision Trees.- On Automatic Modeling and Use of Domain-Specific Ontologies.- Using Self-Adaptable Probes for Dynamic Parameter Control of Parallel Evolutionary Algorithms.- Robust Inference of Bayesian Networks Using Speciated Evolution and Ensemble.- Mining the Semantic Web: A Logic-Based Methodology.- Analysis of Textual Data with Multiple Classes.- SARM - Succinct Association Rule Mining: An Approach to Enhance Association Mining.- Learning the Daily Model of Network Traffic.- ARGUS: Rete + DBMS = Efficient Persistent Profile Matching on Large-Volume Data Streams.- Failing Queries in Distributed Autonomous Information System.- Evaluation of Two Systems on Multi-class Multi-label Document Classification.- Uncertain Knowledge Gathering: An Evolutionary Approach.- Duality in Knowledge Compilation Techniques.- Data Protection in Distributed Database Systems.- A Softened Formulation of Inductive Learning and Its Use for Coronary Disease Data.- Subsystem Based Generalizations of Rough Set Approximations.- Model-Based Cluster Analysis for Web Users Sessions.- On Autonomous k-Means Clustering.- CSI: Clustered Segment Indexing for Efficient Approximate Searching on the Secondary Structure of Protein Sequences.- Using Supervised Clustering to Enhance Classifiers.-Modelling Good Entry Pages on the Web.- A Query Expression and Processing Technique for an XML Search Engine.- Adapting the Object Role Modelling Method for Ontology Modelling.- Identifying Content Blocks from Web Documents.- Building the Data Warehouse of Frequent Itemsets in the DWFIST Approach.- Normal Forms for Knowledge Compilation.- On the Approximate Division of Fuzzy Relations.- Efficient Learning of Pseudo-Boolean Functions from Limited Training Data.- Discovering Partial Periodic Sequential Association Rules with Time Lag in Multiple Sequences for Prediction.- Mining and Filtering Multi-level Spatial Association Rules with ARES.- Association Reducts: A Framework for Mining Multi-attribute Dependencies.- Frequent Pattern Mining with Preferences-Utility Functions Approach.- Semantic-Based Access to Digital Document Databases.- Statistical Database Modeling for Privacy Preserving Database Generation.- Scalable Inductive Learning on Partitioned Data.- Agent-Based Home Simulation and Control.- Aggregates and Preferences in Logic Programming.- The Chisholm Paradox and the Situation Calculus.- A Logic Approach for LTL System Modification.- Anticipatory Agents Based on Anticipatory Reasoning.- Extracting Emotions from Music Data.- An Intelligent System for Assisting Elderly People.- Multi-strategy Instance Selection in Mining Chronic Hepatitis Data.- A Probabilistic Approach to Finding Geometric Objects in Spatial Datasets of the Milky Way.- Towards Ad-Hoc Rule Semantics for Gene Expression Data.- Flexible Pattern Discovery with (Extended) Disjunctive Logic Programming.- Interactive SOM-Based Gene Grouping: An Approach to Gene Expression Data Analysis.- Some Theoretical Properties of Mutual Information for Student Assessments in Intelligent Tutoring Systems.-Cooperative Query Answering for RDF.- Intelligent Information Retrieval for Web-Based Design Data Repository.- Incremental Collaborative Filtering for Highly-Scalable Recommendation Algorithms.- A Distance-Based Algorithm for Clustering Database User Sessions.- User-Interest-Based Document Filtering via Semi-supervised Clustering.- A Filter Feature Selection Method for Clustering.- Automatic Determination of the Numb