LEADER 05533nam 22007695 450 001 9910768442503321 005 20251226203742.0 010 $a3-540-31933-6 024 7 $a10.1007/b136140 035 $a(CKB)1000000000212933 035 $a(SSID)ssj0000315681 035 $a(PQKBManifestationID)11248909 035 $a(PQKBTitleCode)TC0000315681 035 $a(PQKBWorkID)10264546 035 $a(PQKB)10352481 035 $a(DE-He213)978-3-540-31933-7 035 $a(MiAaPQ)EBC3067847 035 $a(PPN)123095093 035 $a(BIP)12317446 035 $a(EXLCZ)991000000000212933 100 $a20100709d2005 u| 0 101 0 $aeng 135 $aurnn#008mamaa 181 $ctxt 182 $cc 183 $acr 200 10$aActive Mining $eSecond International Workshop, AM 2003, Maebashi, Japan, October 28, 2003, Revised Selected Papers /$fedited by Shusaku Tsumoto, Takahira Yamaguchi, Masayuki Numao, Hiroshi Motoda 205 $a1st ed. 2005. 210 1$aBerlin, Heidelberg :$cSpringer Berlin Heidelberg :$cImprint: Springer,$d2005. 215 $a1 online resource (XII, 348 p.) 225 1 $aLecture Notes in Artificial Intelligence,$x2945-9141 ;$v3430 300 $a"This volume contains the papers based on the tutorials of ISMIS 2003 and the papers selected from the regular papers presented at the 2nd International Workshop on Active Mining (AM 2003) held as part of ISMIS 2003"--p. [vii]. 311 08$a3-540-26157-5 320 $aIncludes bibliographical references and index. 327 $aOverview -- Active Mining Project: Overview -- Tutorial Papers -- Computational and Statistical Methods in Bioinformatics -- Indexing and Mining Audiovisual Data -- Active Information Collection -- Relevance Feedback Document Retrieval Using Support Vector Machines -- Micro View and Macro View Approaches to Discovered Rule Filtering -- Mining Chemical Compound Structure Data Using Inductive Logic Programming -- First-Order Rule Mining by Using Graphs Created from Temporal Medical Data -- Active Data Mining -- Extracting Diagnostic Knowledge from Hepatitis Dataset by Decision Tree Graph-Based Induction -- Data Mining Oriented CRM Systems Based on MUSASHI: C-MUSASHI -- Investigation of Rule Interestingness in Medical Data Mining -- Experimental Evaluation of Time-Series Decision Tree -- Spiral Multi-aspect Hepatitis Data Mining -- Sentence Role Identification in Medline Abstracts: Training Classifier with Structured Abstracts -- CHASE 2 ? Rule Based Chase Algorithm for Information Systems of Type ? -- Active User Reaction -- Empirical Comparison of Clustering Methods for Long Time-Series Databases -- Spiral Mining Using Attributes from 3D Molecular Structures -- Classification of Pharmacological Activity of Drugs Using Support Vector Machine -- Cooperative Scenario Mining from Blood Test Data of Hepatitis B and C -- Integrated Mining for Cancer Incidence Factors from Healthcare Data. 330 $aThis volume contains the papers selected for presentation at the 2nd Inter- tional Workshop on Active Mining (AM 2003) which was organized in conju- tion with the 14th International Symposium on Methodologies for Intelligent Systems (ISMIS 2003), held in Maebashi City, Japan, 28-31 October, 2003. The workshop was organized by the Maebashi Institute of Technology in - operation with the Japanese Society for Arti'cial Intelligence. It was sponsored by the Maebashi Institute of Technology, the Maebashi Convention Bureau, the Maebashi City Government, the Gunma Prefecture Government, JSAI SIGKBS (Japanese Arti'cial Intelligence Society, Special Interest Group on Knowledge- Based Systems), a Grant-in-Aid for Scienti'c Research on Priority Areas (No. 759) "Implementation of Active Mining in the Era of Information Flood," US AFOSR/AOARD, the Web Intelligence Consortium (Japan), the Gunma Inf- mation Service Industry Association, and Ryomo Systems Co., Ltd. ISMIS is a conference series that was started in 1986 in Knoxville, Tennessee. SincethenithasbeenheldinCharlotte(NorthCarolina),Knoxville(Tennessee), Torin (Italy), Trondheim (Norway), Warsaw (Poland), Zakopane (Poland), and Lyon (France). The objective of this workshop was to gather researchers as well as prac- tioners who are working on various research ?elds of active mining, share ha- learned experiences, and shed light on the future development of active mining. 410 0$aLecture Notes in Artificial Intelligence,$x2945-9141 ;$v3430 606 $aDatabase management 606 $aArtificial intelligence 606 $aAlgorithms 606 $aMedical informatics 606 $aBioinformatics 606 $aDatabase Management 606 $aArtificial Intelligence 606 $aAlgorithms 606 $aHealth Informatics 606 $aBioinformatics 615 0$aDatabase management. 615 0$aArtificial intelligence. 615 0$aAlgorithms. 615 0$aMedical informatics. 615 0$aBioinformatics. 615 14$aDatabase Management. 615 24$aArtificial Intelligence. 615 24$aAlgorithms. 615 24$aHealth Informatics. 615 24$aBioinformatics. 676 $a006.3/12 701 $aTsumoto$b Shusaku$f1963-$01756814 712 12$aInternational Symposium on Methodologies for Intelligent Systems$d(14th :$f2003 :$eMaebashi-shi, Japan) 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910768442503321 996 $aActive mining$94202568 997 $aUNINA