Data Mining Theory, Methodology, Techniques, and Applications - gebunden oder broschiert

EAN (ISBN-13): 9783540325475
ISBN (ISBN-10): 3540325476
Gebundene Ausgabe
Taschenbuch
Erscheinungsjahr: 2006
Herausgeber: Springer Berlin
331 Seiten
Gewicht: 0,525 kg
Sprache: eng/Englisch

Buch in der Datenbank seit 2007-04-12T14:33:39+02:00 (Vienna)
Detailseite zuletzt geändert am 2023-03-23T17:11:24+01:00 (Vienna)
ISBN/EAN: 9783540325475

ISBN - alternative Schreibweisen:
3-540-32547-6, 978-3-540-32547-5
Alternative Schreibweisen und verwandte Suchbegriffe:
Autor des Buches: simeon, data mining, graham, williams
Titel des Buches: theory data, methodology and science, lecture notes data mining, technique, theory applications, lecture notes computer science, lecture notes artificial intelligence

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Daten vom Verlag:

Autor/in: Graham J. Williams; Simeon J. Simoff
Titel: Lecture Notes in Computer Science; Lecture Notes in Artificial Intelligence; Data Mining - Theory, Methodology, Techniques, and Applications
Verlag: Springer; Springer Berlin
331 Seiten
Erscheinungsjahr: 2006-02-20
Berlin; Heidelberg; DE
Sprache: Englisch
53,49 € (DE)
54,99 € (AT)
59,00 CHF (CH)
Available
XI, 331 p.

BC; Hardcover, Softcover / Informatik, EDV/Informatik; Datenbanken; Verstehen; Informatik; Augmented Reality; Hidden Markov Model; LA; association rules mining; classification; constraint-based mining; data analysis; data linkage; data mining; database management; global patterns; programming; rule discovery; system development; visualization; Database Management; Artificial Intelligence; Theory of Computation; Information Storage and Retrieval; Automated Pattern Recognition; Künstliche Intelligenz; Theoretische Informatik; Informationsrückgewinnung, Information Retrieval; Data Warehousing; Mustererkennung; EA

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.