人工智能与认知科学／会议录Artificial intelligence and cognitive science

2002-12  

Springer  

Michael O'Neill  

245  

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The LNAI series reports state-of-the-art results in artificial intelligence re-search，development，and education，at a high level and in both printed and electronic form. Enjoying tight cooperation with the R＆D community，with numerous individuals，as well as with prestigious organizations and societies，LNAI has grown into the most comprehensive artificial intelligence research forum available. The scope of LNAI spans the whole range of artificial intelligence and intelli-gent information processing including interdisciplinary topics in a variety ofapplication fields. The type of material published traditionally includes proceedings（published in time for the respective conference） post-proceedings（consisting of thoroughly revised final full papers） research monographs（which may be based on PhD work）

Regular Papers On the Usefulness of Extracting Syntactic Dependencies for Text Indexing Using Latent Semantic Indexing as a Measure of Conceptual Association for Noun Compound Disambiguation RADAR: Finding Analogies Using Attributes of Structure Classifying Languages Based on Speech Rhythm Finding Agents in a Two-Dimensional Boolean STaM Neuro-symbolic System for Forecasting Red Tides Improved Learning for Hidden Markov Models Using PenalizedTraining Recovering High-Level Structure of Software Systems Using a Minimum Description Length Principle A System for Multi-agent Information Retrieval All There Is to the Mind Is to Have the Right Genes, or, Consciousness as a Form of Genetic Engineering Towards Robust Collaborative Filtering GVR: A New Genetic Representation for the Vehicle Routing Problem . An Empirical Comparison of Particle Swarm and Predator Prey Optimisation Data Mining Support for Case-Based Collaborative Recommendation The Feasibility of Machine Learning for Query Answering An Experiment in Two Domains Meta-knowledge Annotation for Efficient Natural-Language Question-AnsweringConcise Papers Financial Time Series Modelling Using Neural Networks: An Assessment of the Utility of a Stacking Methodology Experiments in Sparsity Reduction: Using Clustering in Collaborative Recommenders Identification of Visual Features Using a Neural Version of Exploratory Projection Pursuit How People Compare an Item's Placement in Two Alternative Categories Investigations into Market Index Trading Models Using Evolutionary Automatic Programming An Interactive Story Engine Coherence, Explanation, and Bayesian Networks Combining Case-Based Reasoning and Analogical Reasoning in Software Design……Author Index

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