Discovery science : 8th International Conference, DS 2005, Singapore, October 8-11, 2005 : proceedings

書誌事項

Discovery science : 8th International Conference, DS 2005, Singapore, October 8-11, 2005 : proceedings

[Achim Hoffmann, Hiroshi Motoda, Tobias Scheffer (eds.)]

(Lecture notes in computer science, 3735 . Lecture notes in artificial intelligence)

Springer, c2005

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注記

Inlcudes bibliographical references and index

内容説明・目次

内容説明

This volume contains the papers presented at the 8th International Conference onDiscoveryScience(DS2005)heldinSingapore,RepublicofSingapore,during the days from 8-11 of October 2005. The main objective of the Discovery Science (DS) conference series is to p- vide an open forum for intensive discussions and the exchange of new ideas and information among researchers working in the area of automating scienti?c d- covery or working on tools for supporting the human process of discovery in science. It has been a successful arrangement in the past to co-locate the DS conference with the International Conference on Algorithmic Learning Theory (ALT). This combination of ALT and DS allows for a comprehensive treatment ofthewholerange,fromtheoreticalinvestigationstopracticalapplications.C- tinuing in this tradition, DS 2005 was co-located with the 16th ALT conference (ALT2005).TheproceedingsofALT 2005werepublished asa twinvolume3734 of the LNCS series. TheInternationalSteeringCommitteeoftheDiscoveryScienceconference- ries providedimportantadviceon a number ofissues during the planning of D- coveryScience2005.ThemembersoftheSteeringCommiteeareHiroshiMotoda, (Osaka University), Alberto Apostolico (Purdue University), Setsuo Arikawa (Kyushu University), Achim Ho? mann (University of New South Wales), Klaus P. Jantke (DFKI and FIT Leipzig, Germany), Massimo Melucci (U- versityofPadua),Masahiko Sato(Kyoto University),Ayumi Shinohara(Tohoku University),EinoshinSuzuki(YokohamaNationalUniversity),andThomasZe- mann (Hokkaido University). We received 112 full paper submissions out of which 21 long papers (up to 15 pages), 7 regular papers (up to 9 pages), and 9 project reports (3 pages) were acceptedforpresentationandarepublished inthis volume.Eachsubmissionwas reviewed by at least two members of the Program Committee of international expertsinthe?eld.Theselectionwasmadeaftercarefulevaluationofeachpaper based on originality, technical quality, relevance to the ?eld of discovery science, and clarity.

目次

Invited Papers.- Invention and Artificial Intelligence.- Algorithms and Software for Collaborative Discovery from Autonomous, Semantically Heterogeneous, Distributed Information Sources.- Training Support Vector Machines via SMO-Type Decomposition Methods.- The Robot Scientist Project.- The Arrowsmith Project: 2005 Status Report.- Regular Contributions - Long Papers.- Practical Algorithms for Pattern Based Linear Regression.- Named Entity Recognition for the Indonesian Language: Combining Contextual, Morphological and Part-of-Speech Features into a Knowledge Engineering Approach.- Bias Management of Bayesian Network Classifiers.- A Bare Bones Approach to Literature-Based Discovery: An Analysis of the Raynaud's/Fish-Oil and Migraine-Magnesium Discoveries in Semantic Space.- Assisting Scientific Discovery with an Adaptive Problem Solver.- Cross-Language Mining for Acronyms and Their Completions from the Web.- Mining Frequent ?-Free Patterns in Large Databases.- An Experiment with Association Rules and Classification: Post-Bagging and Conviction.- Movement Analysis of Medaka (Oryzias Latipes) for an Insecticide Using Decision Tree.- Support Vector Inductive Logic Programming.- Measuring Over-Generalization in the Minimal Multiple Generalizations of Biosequences.- The q-Gram Distance for Ordered Unlabeled Trees.- Monotone Classification by Function Decomposition.- Learning On-Line Classification via Decorrelated LMS Algorithm: Application to Brain-Computer Interfaces.- An Algorithm for Mining Implicit Itemset Pairs Based on Differences of Correlations.- Pattern Classification via Single Spheres.- SCALETRACK: A System to Discover Dynamic Law Equations Containing Hidden States and Chaos.- Exploring Predicate-Argument Relations for Named Entity Recognition in the Molecular Biology Domain.- Massive Biomedical Term Discovery.- Active Constrained Clustering by Examining Spectral Eigenvectors.- Learning Ontology-Aware Classifiers.- Regular Contributions - Regular Papers.- Automatic Extraction of Proteins and Their Interactions from Biological Text.- A Data Analysis Approach for Evaluating the Behavior of Interestingness Measures.- Unit Volume Based Distributed Clustering Using Probabilistic Mixture Model.- Finding Significant Web Pages with Lower Ranks by Pseudo-Clique Search.- CLASSIC'CL: An Integrated ILP System.- Detecting and Revising Misclassifications Using ILP.- Project Reports.- Self-generation of Control Rules Using Hierarchical and Nonhierarchical Clustering for Coagulant Control of Water Treatment Plants.- A Semantic Enrichment of Data Tables Applied to Food Risk Assessment.- Knowledge Discovery Through Composited Visualization, Navigation and Retrieval.- A Tabu Clustering Method with DHB Operation and Mergence and Partition Operation.- Discovering User Preferences by Using Time Entries in Click-Through Data to Improve Search Engine Results.- Network Boosting for BCI Applications.- Rule-Based FCM: A Relational Mapping Model.- Effective Classifier Pruning with Rule Information.- Text Mining for Clinical Chinese Herbal Medical Knowledge Discovery.

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