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Advances in knowledge discovery and data mining : 5th Pacific-Asia Conference, PAKDD 2001, Hong Kong, China, April 16-18, 2001 : proceedings

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Author: Pacific-Asia Conference on Knowledge Discovery and Data Mining (5th : 2001 : Hong Kong, China), Cheung, David, 1949-, Williams, Graham J, Li, Qing, 1962-

Added by: sketch

Added Date: 2015-12-30

Language: eng

Subjects: Database management, Database searching, Data mining

Publishers: Berlin ; New York : Springer

Collections: journals contributions, journals

ISBN Number: 3540419101

Pages Count: 300

PPI Count: 300

PDF Count: 1

Total Size: 303.12 MB

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Advances in Knowledge Discovery and Data Mining: 5th Pacific-Asia Conference, PAKDD 2001 Hong Kong, China, April 16–18, 2001 Proceedings
Author: David Cheung, Graham J. Williams, Qing Li
Published by Springer Berlin Heidelberg
ISBN: 978-3-540-41910-5
DOI: 10.1007/3-540-45357-1

Table of Contents:

  • Incompleteness in Data Mining
  • Mining E-Commerce Data: The Good, the Bad, and the Ugly
  • Seamless Integration of Data Mining with DBMS and Applications
  • Applying Pattern Mining to Web Information Extraction
  • Empirical Study of Recommender Systems Using Linear Classifiers
  • iJADE eMiner - A Web-Based Mining Agent Based on Intelligent Java Agent Development Environment (iJADE) on Internet Shopping
  • A Characterized Rating Recommend System
  • Discovery of Frequent Tree Structured Patterns in Semistructured Web Documents
  • Text Categorization Using Weight Adjusted k-Nearest Neighbor Classification
  • Predictive Self-Organizing Networks for Text Categorization
  • Meta-learning Models for Automatic Textual Document Categorization
  • Efficient Algorithms for Concept Space Construction
  • Topic Detection, Tracking, and Trend Analysis Using Self-Organizing Neural Networks
  • Automatic Hypertext Construction through a Text Mining Approach by Self-Organizing Maps
  • Semantic Expectation-Based Causation Knowledge Extraction: A Study on Hong Kong Stock Movement Analysis
  • A Toolbox Approach to Flexible and Efficient Data Mining
  • Determining Progression in Glaucoma Using Visual Fields
  • Seabreeze Prediction Using Bayesian Networks
  • Semi-supervised Learning in Medical Image Database
  • On Application of Rough Data Mining Methods to Automatic Construction of Student Models

Includes bibliographical references and index

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