Discovery science : 7th International Conference, DS 2004, Padova, Italy, October 2-5, 2004 : proceedings

書誌事項

Discovery science : 7th International Conference, DS 2004, Padova, Italy, October 2-5, 2004 : proceedings

Einoshin Suzuki, Setsuo Arikawa (eds.)

(Lecture notes in computer science, 3245 . Lecture notes in artificial intelligence)

Springer, c2004

タイトル別名

Discovery science : 7th International Conference, DS 2004, Padova, Italy, October 2004 : proceedings

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注記

Includes bibliographical references and index

内容説明・目次

内容説明

This volume contains the papers presented at the 7th International Conference on Discovery Science (DS 2004) held at the University of Padova, Padova, Italy, during 2-5 October 2004. The main objective of the discovery science (DS) conference series is to p- videanopenforumforintensivediscussionsandtheexchangeofnewinformation amongresearchersworkingintheareaofdiscoveryscience. Ithasbecomeagood custom over the years that the DS conference is held in parallel with the Int- national Conference on Algorithmic Learning Theory (ALT). This co-location has been valuable for the DS conference in order to enjoy synergy between c- ferences devoted to the same objective of computational discovery but from di?erent aspects. Continuing the good tradition, DS 2004 was co-located with the 15th ALT conference (ALT 2004) and was followed by the 11th Symposium on String Processing and Information Retrieval (SPIRE 2004). The agglome- tion of the three international conferences together with the satellite meetings was called Dialogues 2004, in which we enjoyed fruitful interaction among - searchers and practitioners working in various ?elds of computational discovery. The proceedings of ALT 2004 and SPIRE 2004 were published as volume 3244 of the LNAI series and volume 3246 of the LNCS series, respectively. The DS conference series has been supervised by the international ste- ing committee chaired by Hiroshi Motoda (Osaka University, Japan). The other members are Alberto Apostolico (University of Padova, Italy and Purdue U- versity, USA), Setsuo Arikawa (Kyushu University, Japan), Achim Ho?mann (UNSW, Australia), Klaus P. Jantke (DFKI, Germany), Masahiko Sato (- oto University, Japan), Ayumi Shinohara (Kyushu University, Japan), Carl H.

目次

Long Papers.- Predictive Graph Mining.- An Efficient Algorithm for Enumerating Closed Patterns in Transaction Databases.- Finding Optimal Pairs of Cooperative and Competing Patterns with Bounded Distance.- Mining Noisy Data Streams via a Discriminative Model.- CorClass: Correlated Association Rule Mining for Classification.- Maximum a Posteriori Tree Augmented Naive Bayes Classifiers.- Improving Prediction of Distance-Based Outliers.- Detecting Outliers via Logical Theories and Its Data Complexity.- Fast Hierarchical Clustering Algorithm Using Locality-Sensitive Hashing.- Measuring the Similarity for Heterogenous Data: An Ordered Probability-Based Approach.- Constructive Inductive Learning Based on Meta-attributes.- Resemblance Coefficient and a Quantum Genetic Algorithm for Feature Selection.- Extracting Positive Attributions from Scientific Papers.- Enhancing SVM with Visualization.- An Associative Information Retrieval Based on the Dependency of Term Co-occurrence.- On the Convergence of Incremental Knowledge Base Construction.- Privacy Problems with Anonymized Transaction Databases.- A Methodology for Biologically Relevant Pattern Discovery from Gene Expression Data.- Using the Computer to Study the Dynamics of the Handwriting Processes.- Product Recommendation in e-Commerce Using Direct and Indirect Confidence for Historical User Sessions.- Regular Papers.- Optimal Discovery of Subword Associations in Strings.- Tiling Databases.- A Clustering of Interestingness Measures.- Extracting Minimal and Closed Monotone DNF Formulas.- Characterizations of Multivalued Dependencies and Related Expressions.- Outlier Handling in the Neighbourhood-Based Learning of a Continuous Class.- A New Clustering Algorithm Based On Cluster Validity Indices.- An Efficient Rules Induction Algorithm for Rough Set Classification.- Analysing the Trade-Off Between Comprehensibility and Accuracy in Mimetic Models.- Generating AVTs Using GA for Learning Decision Tree Classifiers with Missing Data.- Using WWW-Distribution of Words in Detecting Peculiar Web Pages.- DHT Facilitated Web Service Discovery Incorporating Semantic Annotation.- Discovering Relationships Among Catalogs.- Reasoning-Based Knowledge Extraction for Text Classification.- A Useful System Prototype for Intrusion Detection - Architecture and Experiments.- Discovery of Hidden Similarity on Collaborative Filtering to Overcome Sparsity Problem.- Seamlessly Supporting Combined Knowledge Discovery and Query Answering: A Case Study.- A Structuralist Approach Towards Computational Scientific Discovery.- Extracting Modal Implications and Equivalences from Cognitive Minds.

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