LEADER 09543nam 22008655 450 001 9910143873203321 005 20221025185543.0 010 $a3-540-36175-8 024 7 $a10.1007/3-540-36175-8 035 $a(CKB)1000000000212017 035 $a(SSID)ssj0000320991 035 $a(PQKBManifestationID)11229969 035 $a(PQKBTitleCode)TC0000320991 035 $a(PQKBWorkID)10258844 035 $a(PQKB)11467080 035 $a(DE-He213)978-3-540-36175-6 035 $a(MiAaPQ)EBC3072832 035 $a(PPN)155178938 035 $a(Association for Computing Machinery)10.5555/1760894 035 $a(EXLCZ)991000000000212017 100 $a20121227d2003 u| 0 101 0 $aeng 135 $aurnn#008mamaa 181 $ctxt 182 $cc 183 $acr 200 10$aAdvances in Knowledge Discovery and Data Mining $e7th Pacific-Asia Conference, PAKDD 2003. Seoul, Korea, April 30 - May 2, 2003, Proceedings /$fedited by Kyu-Young Whang, Jongwoo Jeon, Kyuseok Shim, Jaideep Srivatava 205 $a1st ed. 2003. 210 1$aBerlin, Heidelberg :$cSpringer Berlin Heidelberg :$cImprint: Springer,$d2003. 215 $a1 online resource (XVIII, 614 p.) 225 1 $aLecture Notes in Artificial Intelligence ;$v2637 300 $aBibliographic Level Mode of Issuance: Monograph 311 $a3-540-04760-3 320 $aIncludes bibliographical references at the end of each chapters and index. 327 $aIndustrial Papers (Invited) -- Data Mining as an Automated Service -- Trends and Challenges in the Industrial Applications of KDD -- Stream Mining I -- Finding Event-Oriented Patterns in Long Temporal Sequences -- Mining Frequent Episodes for Relating Financial Events and Stock Trends -- Graph Mining -- An Efficient Algorithm of Frequent Connected Subgraph Extraction -- Classifier Construction by Graph-Based Induction for Graph-Structured Data -- Clustering I -- Comparison of the Performance of Center-Based Clustering Algorithms -- Automatic Extraction of Clusters from Hierarchical Clustering Representations -- Text Mining -- Large Scale Unstructured Document Classification Using Unlabeled Data and Syntactic Information -- Extracting Shared Topics of Multiple Documents -- An Empirical Study on Dimensionality Optimization in Text Mining for Linguistic Knowledge Acquisition -- A Semi-supervised Algorithm for Pattern Discovery in Information Extraction from Textual Data -- Bio Mining -- Mining Patterns of Dyspepsia Symptoms Across Time Points Using Constraint Association Rules -- Predicting Protein Structural Class from Closed Protein Sequences -- Learning Rules to Extract Protein Interactions from Biomedical Text -- Predicting Protein Interactions in Human by Homologous Interactions in Yeast -- Web Mining -- Mining the Customer?s Up-To-Moment Preferences for E-commerce Recommendation -- A Graph-Based Optimization Algorithm for Website Topology Using Interesting Association Rules -- A Markovian Approach for Web User Profiling and Clustering -- Extracting User Interests from Bookmarks on the Web -- Stream Mining II -- Mining Frequent Instances on Workflows -- Real Time Video Data Mining for Surveillance Video Streams -- Distinguishing Causal and Acausal Temporal Relations -- Bayesian Networks -- Online Bayes Point Machines -- Exploiting Hierarchical Domain Values for Bayesian Learning -- A New Restricted Bayesian Network Classifier -- Clustering II -- AGRID: An Efficient Algorithm for Clustering Large High-Dimensional Datasets -- Multi-level Clustering and Reasoning about Its Clusters Using Region Connection Calculus -- An Efficient Cell-Based Clustering Method for Handling Large, High-Dimensional Data -- Association Rules I -- Enhancing SWF for Incremental Association Mining by Itemset Maintenance -- Reducing Rule Covers with Deterministic Error Bounds -- Evolutionary Approach for Mining Association Rules on Dynamic Databases -- Semi-structured Data Mining -- Position Coded Pre-order Linked WAP-Tree for Web Log Sequential Pattern Mining -- An Integrated System of Mining HTML Texts and Filtering Structured Documents -- A New Sequential Mining Approach to XML Document Similarity Computation -- Classification I -- Optimization of Fuzzy Rules for Classification Using Genetic Algorithm -- Fast Pattern Selection for Support Vector Classifiers -- Averaged Boosting: A Noise-Robust Ensemble Method -- Improving Performance of Decision Tree Algorithms with Multi-edited Nearest Neighbor Rule -- Data Analysis -- HOT: Hypergraph-Based Outlier Test for Categorical Data -- A Method for Aggregating Partitions, Applications in K.D.D. -- Efficiently Computing Iceberg Cubes with Complex Constraints through Bounding -- Extraction of Tag Tree Patterns with Contractible Variables from Irregular Semistructured Data -- Association Rules II -- Step-by-Step Regression: A More Efficient Alternative for Polynomial Multiple Linear Regression in Stream Cube -- Progressive Weighted Miner: An Efficient Method for Time-Constraint Mining -- Mining Open Source Software (OSS) Data Using Association Rules Network -- Parallel FP-Growth on PC Cluster -- Feature Selection -- Active Feature Selection Using Classes -- Electricity Based External Similarity of Categorical Attributes -- Weighted Proportional k-Interval Discretization for Naive-Bayes Classifiers -- Dealing with Relative Similarity in Clustering: An Indiscernibility Based Approach -- Stream Mining III -- Considering Correlation between Variables to Improve Spatiotemporal Forecasting -- Correlation Analysis of Spatial Time Series Datasets: A Filter-and-Refine Approach -- When to Update the Sequential Patterns of Stream Data? -- Clustering III -- A New Clustering Algorithm for Transaction Data via Caucus -- DBRS: A Density-Based Spatial Clustering Method with Random Sampling -- Optimized Clustering for Anomaly Intrusion Detection -- Classification II -- Finding Frequent Subgraphs from Graph Structured Data with Geometric Information and Its Application to Lossless Compression -- Upgrading ILP Rules to First-Order Bayesian Networks -- A Clustering Validity Assessment Index. 330 $aThe 7th Pacific Asia Conference on Knowledge Discovery and Data Mining (PAKDD) was held from April 30 to May 2, 2003 in the Convention and Exhibition Center (COEX), Seoul, Korea. The PAKDD conference is a major forum for academic researchers and industry practitioners in the Pacific Asia region to share original research results and development experiences from different KDD-related areas such as data mining, data warehousing, machine learning, databases, statistics, knowledge acquisition and discovery, data visualization, and knowledge-based systems. The conference was organized by the Advanced Information Technology Research Center (AITrc) at KAIST and the Statistical Research Center for Complex Systems (SRCCS) at Seoul National University. It was sponsored by the Korean Datamining Society (KDMS), the Korea Information Science Society (KISS), the United States Air Force Office of Scientific Research, the Asian Office of Aerospace Research & Development, and KAIST. It was held with cooperation from ACM?s Special Group on Knowledge Dis- very and Data Mining (SIGKDD). 410 0$aLecture Notes in Artificial Intelligence ;$v2637 517 3 $aPAKDD '03 606 $aData structures (Computer science) 606 $aArtificial intelligence 606 $aMathematical statistics 606 $aDatabase management 606 $aInformation storage and retrieval 606 $aApplication software 606 $aData Structures and Information Theory$3https://scigraph.springernature.com/ontologies/product-market-codes/I15009 606 $aArtificial Intelligence$3https://scigraph.springernature.com/ontologies/product-market-codes/I21000 606 $aProbability and Statistics in Computer Science$3https://scigraph.springernature.com/ontologies/product-market-codes/I17036 606 $aDatabase Management$3https://scigraph.springernature.com/ontologies/product-market-codes/I18024 606 $aInformation Storage and Retrieval$3https://scigraph.springernature.com/ontologies/product-market-codes/I18032 606 $aInformation Systems Applications (incl. Internet)$3https://scigraph.springernature.com/ontologies/product-market-codes/I18040 615 0$aData structures (Computer science). 615 0$aArtificial intelligence. 615 0$aMathematical statistics. 615 0$aDatabase management. 615 0$aInformation storage and retrieval. 615 0$aApplication software. 615 14$aData Structures and Information Theory. 615 24$aArtificial Intelligence. 615 24$aProbability and Statistics in Computer Science. 615 24$aDatabase Management. 615 24$aInformation Storage and Retrieval. 615 24$aInformation Systems Applications (incl. Internet). 676 $a005.74 702 $aWhang$b Kyu-Young$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aJeon$b Jongwoo$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aShim$b Kyuseok$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aSrivatava$b Jaideep$4edt$4http://id.loc.gov/vocabulary/relators/edt 712 12$aPacific-Asia Conference on Knowledge Discovery and Data Mining 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910143873203321 996 $aAdvances in Knowledge Discovery and Data Mining$9772012 997 $aUNINA