知識獲得和管理的進展LNCS-4303

內(nèi)容概要

This book constitutes the thoroughly refereed post-proceedings of the 2006 Pacific Rim Knowledge Acquisition Workshop, PKAW 2006, held in Guilin, China in August 2006 as part of 9th Pacific Rim International Conference on Artificial Intelligence, PRICAI 2006.　　The 21 revised full papers and 6 revised short papers presented together with 4 invited talks were carefully reviewed and selected from 81 submissions. The papers are organized in topical sections on ontology and knowledge acquisition, algorithm approaches to knowledge acquisition, incremental knowledge acquisition and RDR, knowledge acquisition and applications, as well as machine learning and data mining.

書籍目錄

PART I: Regular Papers  Ontology and Knowledge Acquisition　　Visual Knowledge Annotation and Management by Using Qualitative　Spatial Information　　Ad-Hoc and Personal Ontologies: A Prototyping Approach to Ontology　Engineering　　Relating Business Process Models to Goal-Oriented Requirements　Models in KAOS  　Algorithm Approaches to Knowledge Acquisition　　Heuristic and Rule-Based Knowledge Acquisition: Classification　of Numeral Strings in Text　　RFID Tag Based Library Marketing for Improving Patron Services　　Extracting Discriminative Patterns from Graph Structured Data Using　Constrained Search　　Evaluating Learning Algorithms with Meta-learning Schemes for a Rule　Evaluation Support Method Based on Objective Indices　　　Training Classifiers for Unbalanced Distribution and Cost-Sensitive　Domains with ROC Analysis　　Revealing Themes and Trends in the Knowledge Domain's Intellectual　Structure　Incremental Knowledge Acquisition and RDR　　Evaluation of the FastFIX Prototype 5Cs CARD System　　Intelligent Decision Support for Medication Review　　A Hybrid Browsing Mechanism Using Conceptual Scales　Knowledge Acquisition and Applications　　Knowledge Representation for Video Assisted by Domain-Specific　Ontology　　An Ontological Infrastructure for the Semantic Integration of Clinical　Archetypes　　Improvement of Air Handling Unit Control Performance Using　Reinforcement Learning　Machine Learning and Data Mining　　Optimizing Dissimilarity-Based Classifiers Using a Newly Modified　Hausdorff Distance　　A New Model for Classifying DNA Code Inspired by Neural Networks　and FSA　　Improvements on Common Vector Approach Using k-Clustering　Method　　The Method for the Unknown Word ClassificationPART II:Regular Papers(6-8Pages)Author Index

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