LEADER 03324nam 2200601 a 450 001 9910484838003321 005 20200520144314.0 010 $a3-540-31351-6 024 7 $a10.1007/11615576 035 $a(CKB)1000000000232771 035 $a(SSID)ssj0000316987 035 $a(PQKBManifestationID)11258588 035 $a(PQKBTitleCode)TC0000316987 035 $a(PQKBWorkID)10287065 035 $a(PQKB)11372535 035 $a(DE-He213)978-3-540-31351-9 035 $a(MiAaPQ)EBC3068391 035 $a(PPN)123130662 035 $a(EXLCZ)991000000000232771 100 $a20051212d2005 uy 0 101 0 $aeng 135 $aurnn|008mamaa 181 $ctxt 182 $cc 183 $acr 200 10$aConstraint-based mining and inductive databases $eEuropean Workshop on Inductive Databases and Constraint Based Mining, Hinterzarten, Germany, March 11-13, 2004 : revised selected papers /$fJean-Francois Boulicaut, Luc De Raedt, Heikki Mannila (eds.) 205 $a1st ed. 2006. 210 $aBerlin $cSpringer$d2005 215 $a1 online resource (X, 404 p.) 225 1 $aLecture notes in computer science. Lecture notes in artificial intelligence,$x0302-9743 ;$v3848 300 $aBibliographic Level Mode of Issuance: Monograph 311 $a3-540-31331-1 320 $aIncludes bibliographical references and index. 327 $aThe Hows, Whys, and Whens of Constraints in Itemset and Rule Discovery -- A Relational Query Primitive for Constraint-Based Pattern Mining -- To See the Wood for the Trees: Mining Frequent Tree Patterns -- A Survey on Condensed Representations for Frequent Sets -- Adaptive Strategies for Mining the Positive Border of Interesting Patterns: Application to Inclusion Dependencies in Databases -- Computation of Mining Queries: An Algebraic Approach -- Inductive Queries on Polynomial Equations -- Mining Constrained Graphs: The Case of Workflow Systems -- CrossMine: Efficient Classification Across Multiple Database Relations -- Remarks on the Industrial Application of Inductive Database Technologies -- How to Quickly Find a Witness -- Relevancy in Constraint-Based Subgroup Discovery -- A Novel Incremental Approach to Association Rules Mining in Inductive Databases -- Employing Inductive Databases in Concrete Applications -- Contribution to Gene Expression Data Analysis by Means of Set Pattern Mining -- Boolean Formulas and Frequent Sets -- Generic Pattern Mining Via Data Mining Template Library -- Inductive Querying for Discovering Subgroups and Clusters. 410 0$aLecture notes in computer science.$pLecture notes in artificial intelligence ;$v3848. 517 3 $aEuropean Workshop on Inductive Databases and Constraint Based Mining 606 $aDatabase management$vCongresses 606 $aDatabase searching$vCongresses 606 $aData mining$vCongresses 615 0$aDatabase management 615 0$aDatabase searching 615 0$aData mining 676 $a005.74 701 $aBoulicaut$b Jean-Francois$01757045 701 $aRaedt$b Luc de$f1964-$01754852 701 $aMannila$b Heikki$0145716 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910484838003321 996 $aConstraint-based mining and inductive databases$94198209 997 $aUNINA