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20180704 $d00RIV SALA AZZURRA sc. 4 2019 $e00UBG4175 20190925 996 $aRivista di diritto dell'impresa$9789301 997 $aUNICAMPANIA LEADER 08231nam 22008295 450 001 9910144161103321 005 20200706000341.0 010 $a3-540-30076-7 024 7 $a10.1007/b99817 035 $a(CKB)1000000000212504 035 $a(DE-He213)978-3-540-30076-2 035 $a(SSID)ssj0000135079 035 $a(PQKBManifestationID)11146468 035 $a(PQKBTitleCode)TC0000135079 035 $a(PQKBWorkID)10056923 035 $a(PQKB)10605353 035 $a(MiAaPQ)EBC3088221 035 $a(PPN)155213822 035 $a(EXLCZ)991000000000212504 100 $a20121227d2004 u| 0 101 0 $aeng 135 $aurnn|008mamaa 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aData Warehousing and Knowledge Discovery $e6th International Conference, DaWaK 2004, Zaragoza, Spain, September 1-3, 2004, Proceedings /$fedited by Yahiko Kambayashi, Mukesh Mohania, Wolfram Wöß 205 $a1st ed. 2004. 210 1$aBerlin, Heidelberg :$cSpringer Berlin Heidelberg :$cImprint: Springer,$d2004. 215 $a1 online resource (XIV, 412 p.) 225 1 $aLecture Notes in Computer Science,$x0302-9743 ;$v3181 300 $aBibliographic Level Mode of Issuance: Monograph 311 $a3-540-22937-X 320 $aIncludes bibliographical references at the end of each chapters and index. 327 $aData Warehousing Design -- Conceptual Design of XML Document Warehouses -- Bringing Together Partitioning, Materialized Views and Indexes to Optimize Performance of Relational Data Warehouses -- GeoDWFrame: A Framework for Guiding the Design of Geographical Dimensional Schemas -- Workload-Based Placement and Join Processing in Node-Partitioned Data Warehouses -- Knowledge Discovery Framework and XML Data Minig -- Novelty Framework for Knowledge Discovery in Databases -- Revisiting Generic Bases of Association Rules -- Mining Maximal Frequently Changing Subtree Patterns from XML Documents -- Discovering Pattern-Based Dynamic Structures from Versions of Unordered XML Documents -- Data Cubes and Queries -- Space-Efficient Range-Sum Queries in OLAP -- Answering Approximate Range Aggregate Queries on OLAP Data Cubes with Probabilistic Guarantees -- Computing Complex Iceberg Cubes by Multiway Aggregation and Bounding -- Multidimensional Schema and Data Aggregation -- An Aggregate-Aware Retargeting Algorithm for Multiple Fact Data Warehouses -- A Partial Pre-aggregation Scheme for HOLAP Engines -- Discovering Multidimensional Structure in Relational Data -- Inductive Databases and Temporal Rules -- Inductive Databases as Ranking -- Inductive Databases of Polynomial Equations -- From Temporal Rules to Temporal Meta-rules -- Industrial Track -- How Is BI Used in Industry?: Report from a Knowledge Exchange Network -- Towards an Adaptive Approach for Mining Data Streams in Resource Constrained Environments -- Data Clustering -- Exploring Possible Adverse Drug Reactions by Clustering Event Sequences -- SCLOPE: An Algorithm for Clustering Data Streams of Categorical Attributes -- Novel Clustering Approach that Employs Genetic Algorithm with New Representation Scheme and Multiple Objectives -- Data Visualization and Exploration -- Categorical Data Visualization and Clustering Using Subjective Factors -- Multidimensional Data Visual Exploration by Interactive Information Segments -- Metadata to Support Transformations and Data & Metadata Lineage in a Warehousing Environment -- Data Classification, Extraction and Interpretation -- Classification Based on Attribute Dependency -- OWDEAH: Online Web Data Extraction Based on Access History -- Data Mining Approaches to Diffuse Large B?Cell Lymphoma Gene Expression Data Interpretation -- Data Semantics -- Deriving Multiple Topics to Label Small Document Regions -- Deriving Efficient SQL Sequences via Read-Aheads -- Diversity in Random Subspacing Ensembles -- Association Rule Mining -- Partitioned Approach to Association Rule Mining over Multiple Databases -- A Tree Partitioning Method for Memory Management in Association Rule Mining -- Mining Interesting Association Rules for Prediction in the Software Project Management Area -- Mining Event Sequences -- PROWL: An Efficient Frequent Continuity Mining Algorithm on Event Sequences -- Algorithms for Discovery of Frequent Superset, Rather Than Frequent Subset -- Pattern Mining -- Improving Direct Counting for Frequent Itemset Mining -- Mining Sequential Patterns with Item Constraints -- Mining Borders of the Difference of Two Datacubes -- Mining Periodic Patterns in Sequence Data. 330 $aWithin thelastfewyears,datawarehousingandknowledgediscoverytechnology has established itself as a key technology for enterprises that wish to improve the quality of the results obtained from data analysis, decision support, and the automatic extraction of knowledge from data. The 6th InternationalConference on Data Warehousing and KnowledgeD- covery (DaWaK 2004) continued a series of successful conferences dedicated to this topic. Its main objective was to bring together researchers and practiti- ers to discuss research issues and experience in developing and deploying data warehousing and knowledge discovery systems, applications, and solutions. The conference focused on the logical and physical design of data wareho- ing and knowledge discovery systems. The scope of the papers covers the most recent and relevant topics in the areas of data cubes and queries, multidim- sionaldatamodels,XMLdatamining,datasemanticsandclustering,association rules, data mining techniques, data analysis and discovery, query optimization, datacleansing,datawarehousedesignandmaintenance,andapplications.These proceedings contain the technical papers selected for presentation at the conf- ence. We received more than 100 papers, including 12 industrial papers, from over 33 countries, and the program committee ?nally selected 40 papers. The conf- ence program included an invited talk by Kazuo Iwano, IBM Tokyo Research Lab, Japan. We would like to thank the DEXA 2004 Workshop General Chairs (Prof. 410 0$aLecture Notes in Computer Science,$x0302-9743 ;$v3181 606 $aData structures (Computer science) 606 $aDatabase management 606 $aInformation storage and retrieval 606 $aApplication software 606 $aComputer networks 606 $aArtificial intelligence 606 $aData Structures and Information Theory$3https://scigraph.springernature.com/ontologies/product-market-codes/I15009 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 606 $aComputer Communication Networks$3https://scigraph.springernature.com/ontologies/product-market-codes/I13022 606 $aArtificial Intelligence$3https://scigraph.springernature.com/ontologies/product-market-codes/I21000 615 0$aData structures (Computer science) 615 0$aDatabase management. 615 0$aInformation storage and retrieval. 615 0$aApplication software. 615 0$aComputer networks. 615 0$aArtificial intelligence. 615 14$aData Structures and Information Theory. 615 24$aDatabase Management. 615 24$aInformation Storage and Retrieval. 615 24$aInformation Systems Applications (incl. Internet). 615 24$aComputer Communication Networks. 615 24$aArtificial Intelligence. 676 $a005.74 702 $aKambayashi$b Yahiko$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aMohania$b Mukesh$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aWöß$b Wolfram$4edt$4http://id.loc.gov/vocabulary/relators/edt 712 12$aDaWaK 2004 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910144161103321 996 $aData Warehousing and Knowledge Discovery$9772048 997 $aUNINA