Data Mining [[electronic resource] ] : Theory, Methodology, Techniques, and Applications / / edited by Graham J. Williams, Simeon J. Simoff

• Record Nr.: UNISA996466164103316
• Pubbl/distr/stampa: Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2006
• ISBN: 3-540-32548-4
• Edizione: [1st ed. 2006.]
• Descrizione fisica: 1 online resource (XI, 331 p.)
• Collana: Lecture Notes in Artificial Intelligence ; ; 3755
• Disciplina: 005.74
• Soggetti: Database management; Artificial intelligence; Computers; Information storage and retrieval; Pattern recognition; Database Management; Artificial Intelligence; Computation by Abstract Devices; Information Storage and Retrieval; Pattern Recognition
• Lingua di pubblicazione: Inglese
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Note generali: Chapters based on the works presented at the Australasian data mining conference series and industry forums.
• Nota di bibliografia: Includes bibliographical references and index.
• Nota di contenuto: 1: State-of-the-Art in Research -- Generality Is Predictive of Prediction Accuracy -- Visualisation and Exploration of Scientific Data Using Graphs -- A Case-Based Data Mining Platform -- Consolidated Trees: An Analysis of Structural Convergence -- K Nearest Neighbor Edition to Guide Classification Tree Learning: Motivation and Experimental Results -- Efficiently Identifying Exploratory Rules’ Significance -- Mining Value-Based Item Packages – An Integer Programming Approach -- Decision Theoretic Fusion Framework for Actionability Using Data Mining on an Embedded System -- Use of Data Mining in System Development Life Cycle -- Mining MOUCLAS Patterns and Jumping MOUCLAS Patterns to Construct Classifiers -- A Probabilistic Geocoding System Utilising a Parcel Based Address File -- Decision Models for ; Record Linkage -- Intelligent Document Filter for the Internet -- Informing the Curious Negotiator: Automatic News Extraction from the Internet -- Text Mining for Insurance Claim Cost Prediction -- An Application of Time-Changing Feature Selection -- A Data Mining Approach to Analyze the Effect of Cognitive Style and Subjective Emotion on the Accuracy of Time-Series Forecasting -- A Multi-level Framework for the Analysis of Sequential Data -- 2: State-of-the-Art in Applications -- Hierarchical Hidden Markov Models: An Application to Health Insurance Data -- Identifying Risk Groups Associated with Colorectal Cancer -- Mining Quantitative Association Rules in Protein Sequences -- Mining X-Ray Images of SARS Patients -- The Scamseek Project – Text Mining for Financial Scams on the Internet -- A Data Mining Approach for Branch and ATM Site Evaluation -- The Effectiveness of Positive Data Sharing in Controlling the Growth of Indebtedness in Hong Kong Credit Card Industry.