Advances in Knowledge Acquisition and Management

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. It covers ontology and knowledge acquisition, algorithm approaches to knowledge acquisition, incremental knowledge acquisition and RDR, as well as machine learning and data mining.

Inhalt

Regular Papers.- 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.- 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.- Evaluation of the FastFIX Prototype 5Cs CARD System.- Intelligent Decision Support for Medication Review.- A Hybrid Browsing Mechanism Using Conceptual Scales.- 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.- 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 Classification.- Regular Papers (6-8 Pages).- An Ontology Supported Approach to Learn Term to Concept Mapping.- Building Corporate Knowledge Through Ontology Integration.- Planning with Domain Rules Based on State-Independent Activation Sets.- Elicitation of Non-functional Requirement Preference for Actors of Usecase from Domain Model.- Enhancing Information Retrieval Using Problem Specific Knowledge.- Acquiring Innovation Knowledge.