The papers in this volume are the refereed application papers presented at AI-2005, the Twenty-fifth SGAI International Conference on Innovative Techniques and Applications of Artificial Intelligence, held in Cambridge in December 2005.
The papers present new and innovative developments in the field, divided into sections on Synthesis and Prediction, Scheduling and Search, Diagnosis and Monitoring, Classification and Design, and Analysis and Evaluation.
This is the thirteenth volume in the Applications and Innovations series. The series serves as a key reference on the use of AI Technology to enable organisations to solve complex problems and gain significant business benefits.
The Technical Stream papers are published as a companion volume under the title Research and Development in Intelligent Systems XXII.
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Application Keynote Address.- Legal Engineering: A structural approach to Improving Legal Quality.- Best Application Paper.- Case-Based Reasoning Investigation of Therapy Inefficacy.- Applied Al in Information Processing.- Hybrid search algorithm applied to the colour quantisation problem.- The Knowledge Bazaar.- Generating Feedback Reports for Adults Taking Basic Skills Tests.- A Neural Network Approach to Predicting Stock Exchange Movements using External Factors.- Techniques for Applied Al.- A Fuzzy Rule-Based Approach for the Collaborative Formation of Design Structure Matrices.- Geometric Proportional Analogies In Topographic Maps: Theory and Application.- Experience with Ripple-Down Rules.- Applying Bayesian Networks for Meteorological Data Mining.- Industrial Applications.- WISE Expert: An Expert System for Monitoring Ship Cargo Handling.- A Camera-Direction Dependent Visual-Motor Coordinate Transformation for a Visually Guided Neural Robot.- An Application of Artificial Intelligence to the Implementation of Virtual Automobile Manufacturing Enterprise.- Medical Applications.- Web-based Medical Teaching using a Multi-Agent System.- Building an Ontology and Knowledge Base of the Human Meridian-Collateral System.- The Effect of Principal Component Analysis on Machine Learning Accuracy with High Dimensional Spectral Data.