Data Mining

Part I: Methodological Approaches; Section 1: Data mining; Learning networks for tornado forecasting: a Bayesian perspective; Outlier detection based on projection-based ordering; On extending F-measure and G-mean metrics to multi-class problems; Multivariate interdependent discretization in discovering the best correlated attribute; Estimation and extension of the Stochastic Schemata Exploiter; Decision making on operational data: a remote approach to distributed data monitoring; A multi-strategy approach for mining multimedia data repositories; Section 2: Text mining; A multi-criteria decision making approach in feature selection for enhancing text categorization; Multilingual text mining; The protein ontology project: structured vocabularies for proteins; Text mining for stock movement predictions: a Malaysian perspective; Medical communication quality in the Italian pharmaceutical industry: measurement and analysis by 'NOOS'; A comparison of two algorithms for discovering repeated word sequences; A genetic algorithm for text mining; The process of sensemaking on the telework virtual community using text mining; Knowledge discovery in large text databases using the MST algorithm; Textual document pre-processing and feature extraction in OLEX; Naive rule induction for text classification based on key-phrases; Renovation of terms adjustment and effective model combination impact on information retrieval performance; Linguistic summaries on small screens; Rule discovery in Web-based educational systems using Grammar-Based Genetic Programming; Part II: Techniques; Section 3: Neural networks and decision trees; Multi-relational data mining in Microsoft SQL Server'; Neural network models for the development and evaluation of new fuels; CC4.5: cost-sensitive decision tree pruning; Cooling Growing Grid: an incremental self-organizing neural network for data exploration; Pleiotropic microarray gene expression data: advanced tandem multivariate data mining; A decision tree classifier for vehicle failure isolation; Section 4: Link analysis; A method for generating aggregated associations between discrete data features; X3-Miner: mining patterns from an XML database; Section 5: Clustering and categorisation; Mining association rules from qualitative and quantitative clustering; HyperClustering: from the digital divide to a GRID e-workspace; DEA implementation and clustering analysis using the K-Means algorithm; A hybrid method to categorize HTML documents; Part III: Applications; Section 6: Consumer and strategic intelligence; Application of technology prospective to business sectorial studies; Discovering common interests and problems to improve working conditions at a large company; The use of knowledge discovery techniques for behavioural scoring; Providing database encryption as a scalable enterprise infrastructure service; National Security and threat awareness; Measuring user satisfaction with intelligent agents: an exploratory study; A clustering approach for knowledge discovery in database marketing; Section 7: Applications in science, engineering and life sciences; Evaluation of clinical prediction rules using a convergence of knowledge-driven and data-driven methods: a semio-fuzzy approach; Evolving neural networks to flow cytometric data interpretation; Classification algorithms and analyzing the functionality of protein families; Mining GPS logs to augment location models; An adaptive Bayesian classification for real-time image analysis in real-time particle monitoring for polymer film manufacturing; Section 8: Applications in business, industry and government; Mining effective design solutions based on a model-driven approach; Application of fuzzy models and neural models in financial time series; E-commerce models for banks' profitability; Sarbanes-Oxley, Basel II, and data mining opportunities in compliance systems; Survival data mining in the telecommunications industries: usefulness and complications; Data mining methods in a metrics-deprived inventory transactions environment; Ecological mining - a case study on dam water quality; Improving effectiveness of Web sites using incremental data mining over clickstreams; Data mining education for external auditors