This book constitutes the refereed proceedings of the Second European Symposium on Principles of Data Mining and Knowledge Discovery, PKDD '98, held in Nantes, France, in September 1998. The volume presents 26 revised papers corresponding to the oral presentations given at the conference; also included are refereed papers corresponding to the 30 poster presentations. These papers were selected from a total of 73 full draft submissions. The papers are organized in topical sections on rule evaluation, visualization, association rules and text mining, KDD process and software, tree construction, sequential and spatial data mining, and attribute selection.
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First Sentence:
A crucial aspect of data mining is that the discovered knowledge (usually expressed in the form of "if-then" rules) should be somehow interesting, where the term interestingness is arguably related to the properties of surprisingness (unexpectedness), usefulness and novelty of the rule [Fayyad et al. 96]. Read the first page Key Phrases - Statistically Improbable Phrases (SIPs): (learn more)
term extraction module, query frontier, surprisingness measure, ranked layer, representative association rules, data access primitives, large textual collections, implicational quantifier, minimum error tree, minimum expected cost criterion, fuzzy modalities, multiple missing values, rule surprisingness, average class entropy, truth preservation condition, original disjunct, conceptual data systems, discretization cost, total misclassification costs, extended functional dependencies, replanning algorithm, surprising exception rules, temporal association rules, equivalence quantifiers, sensitive discretization Key Phrases - Capitalized Phrases (CAPs): (learn more)
Morgan Kaufmann, Object Mining, Menlo Park, Formal Concept Analysis, Department of Computer Science, European Conference, New York, San Mateo, Term Generation, Introduction Knowledge, Management of Data, Document Explorer, Error Diff, Lecture Notes, Term Filtering, Data Archaeology, Fast Discovery of Association Rules, Rough Enough, Springer Verlag, Anders Torvill, Computer Society Press, Journal of Intelligent Information Systems, Kluwer Academic Publishers, University of California, France Abstract New!
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Front Cover | Table of Contents | First Pages | Index | Back Cover | Surprise Me!
A crucial aspect of data mining is that the discovered knowledge (usually expressed in the form of "if-then" rules) should be somehow interesting, where the term interestingness is arguably related to the properties of surprisingness (unexpectedness), usefulness and novelty of the rule [Fayyad et al. 96]. Read the first page Key Phrases - Statistically Improbable Phrases (SIPs): (learn more)
term extraction module, query frontier, surprisingness measure, ranked layer, representative association rules, data access primitives, large textual collections, implicational quantifier, minimum error tree, minimum expected cost criterion, fuzzy modalities, multiple missing values, rule surprisingness, average class entropy, truth preservation condition, original disjunct, conceptual data systems, discretization cost, total misclassification costs, extended functional dependencies, replanning algorithm, surprising exception rules, temporal association rules, equivalence quantifiers, sensitive discretization Key Phrases - Capitalized Phrases (CAPs): (learn more)
Morgan Kaufmann, Object Mining, Menlo Park, Formal Concept Analysis, Department of Computer Science, European Conference, New York, San Mateo, Term Generation, Introduction Knowledge, Management of Data, Document Explorer, Error Diff, Lecture Notes, Term Filtering, Data Archaeology, Fast Discovery of Association Rules, Rough Enough, Springer Verlag, Anders Torvill, Computer Society Press, Journal of Intelligent Information Systems, Kluwer Academic Publishers, University of California, France Abstract New!
Books on Related Topics | Concordance | Text Stats Browse Sample Pages:
Front Cover | Table of Contents | First Pages | Index | Back Cover | Surprise Me!
Citations (learn more)
This book cites 62
books:
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- Advances in Knowledge Discovery and Data Mining (American Association for Artificial Intelligence) by Usama M. Fayyad on 18 pages
- on 6 pages
- Knowledge Discovery in Databases (Aaai Press Copublications) by William Frawley on 6 pages
- Classification and Regression Trees by Leo Breiman on 5 pages
- Pattern Classification and Scene Analysis by Richard O. Duda on 4 pages
See all 62 books this book cites
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