Research and development in knowledge discovery and data mining : Second Pacific-Asia Conference, PAKDD-98, Melbourne, Australia, April 15 17, 1998 : proceedings
This book constitutes the refereed proceedings of the Second Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD-98, held in Melbourne, Australia, in April 1998. The book presents 30 revised full papers selected from a total of 110 submissions; also included are 20 poster presentat...
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| Edice: | Lecture notes in computer science. Lecture notes in artificial intelligence
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| Edition sous un autre format: | • Research and development in knowledge discovery and data mining, Second Pacific-Asia Conference, PAKDD-98, Melbourne, Australia, April 15-17, 1998, proceedings, Xindong Wu, Ramamohanarao Kotagiri, Kevin B. Korb, eds, 1998, New York, Springer, 1 vol. (XVI-425 p.), Lecture notes in computer science, 3-540-64383-4 • Research and Development in Knowledge Discovery and Data Mining, Texte imprimé, 9783662174012 |
Obsah:
- Knowledge acquisition for goal prediction in a multi-user adventure game
- Hybrid data mining systems: The next generation
- Discovering case knowledge using data mining
- Discovery of association rules over ordinal data: A new and faster algorithm and its application to basket analysis
- Effect of data skewness in parallel mining of association rules
- Trend directed learning: A case study
- Interestingness of discovered association rules in terms of neighborhood-based unexpectedness
- Point estimation using the Kullback-Leibler loss function and MML
- Single factor analysis in MML mixture modelling
- Discovering associations in spatial data An efficient medoid based approach
- Data mining using dynamically constructed recurrent fuzzy neural networks
- CCAIIA: Clustering categorical attributes into interesting association rules
- Selective materialization: An efficient method for spatial data cube construction
- Mining market basket data using share measures and characterized itemsets
- Automatic visualization method for visual data mining
- Rough-set inspired approach to knowledge discovery in business databases
- Representative association rules
- Identifying relevant databases for multidatabase mining
- Minimum message length segmentation
- Bayesian classification trees with overlapping leaves applied to credit-scoring
- Contextual text representation for unsupervised knowledge discovery in texts
- Treatment of missing values for association rules
- Mining regression rules and regression trees
- Mining algorithms for sequential patterns in parallel : Hash based approach
- Wavelet transform in similarity paradigm
- Improved rule discovery performance on uncertainty
- Feature mining and mapping of collinear data
- Knowledge discovery in discretionary legaldomains
- Scaling up the rule generation of C4.5
- Data mining based on the generalization distribution table and rough sets
- Constructing personalized information agents
- Towards real time discovery from distributed information sources
- Constructing conceptual scales in formal concept analysis
- The hunter and the hunted Modelling the relationship between web pages and search engines
- An efficient global discretization method
- Learning user preferences on the WEB
- Using rough sets for knowledge discovery in the development of a decision support system for issuing smog alerts
- Empirical results on data dimensionality reduction using the divided self-organizing map
- Mining association rules with linguistic cloud models
- A data mining approach for query refinement
- CFMD: A conflict-free multivariate discretization algorithm
- Characteristic rule induction algorithm for data mining
- Data-mining massive time series astronomical data sets A case study
- Multiple databases, partial reasoning, and knowledge discovery
- Design recovery with data mining techniques
- The CLARET algorithm
- LRTree: A hybrid technique for classifying myocardial infarction data containing unknown attribute values
- Modelling decision tables from data
- A classification and relationship extraction scheme for relational databases based on fuzzy logic
- Mining association rules for estimation and prediction
- Rule generalization by condition combination.