LEADER 08145nam 22008535 450 001 9910484131603321 005 20251226203138.0 010 $a3-540-31698-1 010 $a3-540-29230-6 024 7 $a10.1007/11563983 035 $a(CKB)1000000000213296 035 $a(SSID)ssj0000317235 035 $a(PQKBManifestationID)11247718 035 $a(PQKBTitleCode)TC0000317235 035 $a(PQKBWorkID)10287794 035 $a(PQKB)10938515 035 $a(DE-He213)978-3-540-31698-5 035 $a(MiAaPQ)EBC3067840 035 $a(PPN)123098017 035 $a(BIP)13163589 035 $a(EXLCZ)991000000000213296 100 $a20100319d2005 u| 0 101 0 $aeng 135 $aurnn|008mamaa 181 $ctxt 182 $cc 183 $acr 200 10$aDiscovery Science $e8th International Conference, DS 2005, Singapore, October 8-11, 2005, Proceedings /$fedited by Achim Hoffmann, Hiroshi Motoda, Tobias Scheffer 205 $a1st ed. 2005. 210 1$aBerlin, Heidelberg :$cSpringer Berlin Heidelberg :$cImprint: Springer,$d2005. 215 $a1 online resource (XVI, 404 p.) 225 1 $aLecture Notes in Artificial Intelligence,$x2945-9141 ;$v3735 300 $aBibliographic Level Mode of Issuance: Monograph 311 08$aPrinted edition: 9783540292302 320 $aIncludes bibliographical references and index. 327 $aInvited 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 MolecularBiology 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. 330 $aThis 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. 410 0$aLecture Notes in Artificial Intelligence,$x2945-9141 ;$v3735 606 $aScience$xPhilosophy 606 $aArtificial intelligence 606 $aDatabase management 606 $aInformation storage and retrieval systems 606 $aInformation technology$xManagement 606 $aSocial sciences$xData processing 606 $aPhilosophy of Science 606 $aArtificial Intelligence 606 $aDatabase Management 606 $aInformation Storage and Retrieval 606 $aComputer Application in Administrative Data Processing 606 $aComputer Application in Social and Behavioral Sciences 615 0$aScience$xPhilosophy. 615 0$aArtificial intelligence. 615 0$aDatabase management. 615 0$aInformation storage and retrieval systems. 615 0$aInformation technology$xManagement. 615 0$aSocial sciences$xData processing. 615 14$aPhilosophy of Science. 615 24$aArtificial Intelligence. 615 24$aDatabase Management. 615 24$aInformation Storage and Retrieval. 615 24$aComputer Application in Administrative Data Processing. 615 24$aComputer Application in Social and Behavioral Sciences. 676 $a501 701 $aHoffmann$b Achim$01618538 701 $aMotoda$b Hiroshi$0145437 701 $aScheffer$b Tobias$01756206 712 12$aDS 2005 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910484131603321 996 $aDiscovery science$94202614 997 $aUNINA