LEADER 06412nam 22008055 450 001 996466219803316 005 20200704161213.0 010 $a3-540-45681-3 024 7 $a10.1007/3-540-45681-3 035 $a(CKB)1000000000211752 035 $a(SSID)ssj0000325836 035 $a(PQKBManifestationID)11264621 035 $a(PQKBTitleCode)TC0000325836 035 $a(PQKBWorkID)10264732 035 $a(PQKB)10441942 035 $a(DE-He213)978-3-540-45681-0 035 $a(MiAaPQ)EBC3071606 035 $a(PPN)15516709X 035 $a(EXLCZ)991000000000211752 100 $a20121227d2002 u| 0 101 0 $aeng 135 $aurnn#008mamaa 181 $ctxt 182 $cc 183 $acr 200 10$aPrinciples of Data Mining and Knowledge Discovery$b[electronic resource] $e6th European Conference, PKDD 2002, Helsinki, Finland, August 19?23, 2002, Proceedings /$fedited by Tapio Elomaa, Heikki Mannila, Hannu Toivonen 205 $a1st ed. 2002. 210 1$aBerlin, Heidelberg :$cSpringer Berlin Heidelberg :$cImprint: Springer,$d2002. 215 $a1 online resource (XIV, 514 p.) 225 1 $aLecture Notes in Artificial Intelligence ;$v2431 300 $aBibliographic Level Mode of Issuance: Monograph 311 $a3-540-44037-2 320 $aIncludes bibliographical references and index. 327 $aContributed Papers -- Optimized Substructure Discovery for Semi-structured Data -- Fast Outlier Detection in High Dimensional Spaces -- Data Mining in Schizophrenia Research ? Preliminary Analysis -- Fast Algorithms for Mining Emerging Patterns -- On the Discovery of Weak Periodicities in Large Time Series -- The Need for Low Bias Algorithms in Classification Learning from Large Data Sets -- Mining All Non-derivable Frequent Itemsets -- Iterative Data Squashing for Boosting Based on a Distribution-Sensitive Distance -- Finding Association Rules with Some Very Frequent Attributes -- Unsupervised Learning: Self-aggregation in Scaled Principal Component Space* -- A Classification Approach for Prediction of Target Events in Temporal Sequences -- Privacy-Oriented Data Mining by Proof Checking -- Choose Your Words Carefully: An Empirical Study of Feature Selection Metrics for Text Classification -- Generating Actionable Knowledge by Expert-Guided Subgroup Discovery -- Clustering Transactional Data -- Multiscale Comparison of Temporal Patterns in Time-Series Medical Databases -- Association Rules for Expressing Gradual Dependencies -- Support Approximations Using Bonferroni-Type Inequalities -- Using Condensed Representations for Interactive Association Rule Mining -- Predicting Rare Classes: Comparing Two-Phase Rule Induction to Cost-Sensitive Boosting -- Dependency Detection in MobiMine and Random Matrices -- Long-Term Learning for Web Search Engines -- Spatial Subgroup Mining Integrated in an Object-Relational Spatial Database -- Involving Aggregate Functions in Multi-relational Search -- Information Extraction in Structured Documents Using Tree Automata Induction -- Algebraic Techniques for Analysis of Large Discrete-Valued Datasets -- Geography of Di.erences between Two Classes of Data -- Rule Induction for Classification of Gene Expression Array Data -- Clustering Ontology-Based Metadata in the Semantic Web -- Iteratively Selecting Feature Subsets for Mining from High-Dimensional Databases -- SVM Classification Using Sequences of Phonemes and Syllables -- A Novel Web Text Mining Method Using the Discrete Cosine Transform -- A Scalable Constant-Memory Sampling Algorithm for Pattern Discovery in Large Databases -- Answering the Most Correlated N Association Rules Efficiently -- Mining Hierarchical Decision Rules from Clinical Databases Using Rough Sets and Medical Diagnostic Model -- Efficiently Mining Approximate Models of Associations in Evolving Databases -- Explaining Predictions from a Neural Network Ensemble One at a Time -- Structuring Domain-Specific Text Archives by Deriving a Probabilistic XML DTD -- Separability Index in Supervised Learning -- Invited Papers -- Finding Hidden Factors Using Independent Component Analysis -- Reasoning with Classifiers* -- A Kernel Approach for Learning from Almost Orthogonal Patterns -- Learning with Mixture Models: Concepts and Applications. 410 0$aLecture Notes in Artificial Intelligence ;$v2431 606 $aDatabase management 606 $aArtificial intelligence 606 $aMathematical logic 606 $aMathematical statistics 606 $aNatural language processing (Computer science) 606 $aInformation storage and retrieval 606 $aDatabase Management$3https://scigraph.springernature.com/ontologies/product-market-codes/I18024 606 $aArtificial Intelligence$3https://scigraph.springernature.com/ontologies/product-market-codes/I21000 606 $aMathematical Logic and Formal Languages$3https://scigraph.springernature.com/ontologies/product-market-codes/I16048 606 $aProbability and Statistics in Computer Science$3https://scigraph.springernature.com/ontologies/product-market-codes/I17036 606 $aNatural Language Processing (NLP)$3https://scigraph.springernature.com/ontologies/product-market-codes/I21040 606 $aInformation Storage and Retrieval$3https://scigraph.springernature.com/ontologies/product-market-codes/I18032 615 0$aDatabase management. 615 0$aArtificial intelligence. 615 0$aMathematical logic. 615 0$aMathematical statistics. 615 0$aNatural language processing (Computer science). 615 0$aInformation storage and retrieval. 615 14$aDatabase Management. 615 24$aArtificial Intelligence. 615 24$aMathematical Logic and Formal Languages. 615 24$aProbability and Statistics in Computer Science. 615 24$aNatural Language Processing (NLP). 615 24$aInformation Storage and Retrieval. 676 $a006.3 702 $aElomaa$b Tapio$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aMannila$b Heikki$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aToivonen$b Hannu$4edt$4http://id.loc.gov/vocabulary/relators/edt 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a996466219803316 996 $aPrinciples of data mining and knowledge discovery$9415802 997 $aUNISA