By Aijun An, Nick Cercone, Xiangji Huang (auth.), Eleni Stroulia, Stan Matwin (eds.)
AI 2001 is the 14th within the sequence of Arti cial Intelligence meetings subsidized by means of the Canadian Society for Computational stories of Intelligence/Soci et e - nadienne pour l’ etude de l’intelligence par ordinateur. As used to be the case final yr too, the convention is being held along side the yearly meetings of 2 different Canadian societies, pics Interface (GI 2001) and imaginative and prescient Int- face (VI 2001). We think that the general event should be enriched via this conjunction of meetings. This 12 months is the \silver anniversary" of the convention: the rst Canadian AI convention was once held in 1976 at UBC. in the course of its lifetime, it has attracted Canadian and overseas papers of top of the range from a number of AI study parts. All papers submitted to the convention got at the very least 3 indep- dent experiences. nearly one 3rd have been authorized for plenary presentation on the convention. the easiest paper of the convention may be invited to seem in Computational Intelligence.
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Extra info for Advances in Artificial Intelligence: 14th Biennial Conference of the Canadian Society for Computational Studies of Intelligence, AI 2001 Ottawa, Canada, June 7–9, 2001 Proceedings
18 A. Gerber and C. Russ provide additional advantages. Holonic agents are highly flexible at solving their tasks, having the ability to deal with inevitable change, since they are self-organizing and decentralized. Finally, as an advantage of analysis and building a system, holonically structured MAS exhibit a mapping of conceptual view and operational implementation. The implementation reflects the conceptual structure. g. virtual enterprises, supply webs) by a H-MAS because the holonic agent-based structuring supports their flexible and fluid formation as well as their dissolving.
After collecting features for each two-word candidate, we use mutual information and log-likelihood ratios to extend them to multi-word terms. We experiment with both English and Chinese corpora. Using perplexity, we quantify the definition of a term and we obtain a comparative evaluation of term extraction algorithms. Furthermore, we evaluate the precision and recall of our term extractor by comparing the words in a segmented Chinese corpus with the words extracted by our system. Our evaluation methodology circumvents the problems encountered by previously used human evaluations.
Maintenance of Discovered Association Rules in Large Database: An I ncremental Updating Technique, In Proceedings of the 12th International Conference on Data Engineering, New Orleans, Louisiana, 1996. : A General Incremental Technique for Maintaining Discovered Association Rules, In Proceedings of the Fifth International Conference on Database Systems for Advanced Applications, Melbourne, Australia, jan, 1997. : A Perspective on Databases and Data Mining. First International conference on Knowledge, Discovery and data Mining, Montreal, canada, AAAI Press, 1995, pp.