Advances in Artificial Intelligence

13th Biennial Conference of the Canadian Society for Computational Studies of Intelligence, AI 2000 Montreal, Quebec, ... / Lecture Notes in Artificial Intelligence)

Edición de la obra Advances in Artificial Intelligence

Advances in Artificial Intelligence: 13th Biennial Conference of the Canadian Society for Computational Studies of Intelligence, AI 2000 Montéal, Quebec, Canada, May 14–17, 2000 Proceedings<br />Author: Howard J. Hamilton<br /> Published by Springer Berlin Heidelberg<br /> ISBN: 978-3-540-67557-0<br /> DOI: 10.1007/3-540-45486-1<br /><br />Table of Contents:<p></p><ul><li>Unifying Single-Agent and Two-Player Search </li><li>Are Bees Better than Fruitflies? </li><li>A Constraint Directed Model for Partial Constraint Satisfaction Problems </li><li>Using Noun Phrase Heads to Extract Document Keyphrases </li><li>Expanding the Type Hierarchy with Nonlexical Concepts </li><li>Using Object Influence Areas to Quantitatively Deal with Neighborhood and Perception in Route Descriptions </li><li>An Extendable Natural Language Interface to a Consumer Service Database </li><li>Identifying and Eliminating Irrelevant Instances Using Information Theory </li><li>Keep It Simple: A Case-Base Maintenance Policy Based on Clustering and Information Theory </li><li>On the Integration of Recursive </li><li>Collocation Discovery for Optimal Bilingual Lexicon Development </li><li>The Power of the TSNLP: Lessons from a Diagnostic Evaluation of a Broad-Coverage Parser </li><li>A Parallel Approach to Unified Cognitive Modeling of Language Processing within a Visual Context </li><li>Interact: A Staged Approach to Customer Service Automation </li><li>Towards Very Large Terminological Knowledge Bases: A Case Study from Medicine </li><li>The Use of Ontologies and Meta-knowledge to Facilitate the Sharing of Knowledge in a Multi-agent Personal Communication System </li><li>ASERC - A Genetic Sequencing Operator for Asymmetric Permutation Problems </li><li>CViz: An Interactive Visualization System for Rule Induction </li><li>Learning Pseudo-independent Models: Analytical and Experimental Results </li><li>Learning Rewrite Rules versus Search Control Rules to Improve Plan Quality</li></ul>