Data Mining [electronic resource] : Theory, Methodology, Techniques, and Applications / edited by Graham J. Williams, Simeon J. Simoff.
Contributor(s): Williams, Graham J [editor.] | Simoff, Simeon J [editor.] | SpringerLink (Online service).
Material type: BookSeries: Lecture Notes in Artificial Intelligence: 3755Publisher: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2006Edition: 1st ed. 2006.Description: XI, 331 p. online resource.Content type: text Media type: computer Carrier type: online resourceISBN: 9783540325482.Subject(s): Database management | Artificial intelligence | Computer science | Information storage and retrieval systems | Pattern recognition systems | Database Management | Artificial Intelligence | Theory of Computation | Information Storage and Retrieval | Automated Pattern RecognitionAdditional physical formats: Printed edition:: No title; Printed edition:: No titleDDC classification: 005.74 Online resources: Click here to access online1: 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.
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