Download Advances in Artificial Intelligence: 14th Biennial by Aijun An, Nick Cercone, Xiangji Huang (auth.), Eleni PDF

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 was once the case final 12 months too, the convention is being held along side the yearly meetings of 2 different Canadian societies, images Interface (GI 2001) and imaginative and prescient Int- face (VI 2001). We think that the final event can be enriched by way of 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 quality from various AI learn components. All papers submitted to the convention acquired no less than 3 indep- dent reports. nearly one 3rd have been permitted for plenary presentation on the convention. the simplest paper of the convention should be invited to seem in Computational Intelligence.

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Additional resources 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

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We loop through each good extension g in G. e. either c g or g c). e. g has not been previously A Statistical Corpus-Based Term Extractor 41 extended). For example, suppose that Jones Computer and Computer Publishing are both two-word candidates and that the former is extended to Jones Computer Publishing. Now, suppose that we are attempting to extend Computer Publishing with g = Jones. Since Jones Computer Publishing has already been extracted, we do not want to extend Computer Publishing with g = Jones.

A simple database transaction table for illustrating the idea is given as Table 1. Table 1. The Example Database Transaction table TID 100 200 300 400 500 600 A A B A A A Items BCDF BCDE CD DE CD BCE If we delete transacion 400, and add new transaction 700 B D E, we can get an updated database DB’, which is suitable for FUP2. To compute the large itemsets in the old database (Table 1), Apriori algorithm first generates the candidate set C1 ={A, B, C, D, E, F}, then scans the database to obtain the support of each itemset in C1 .

The CMM agent holds up-to-date data of all co-ordinations run by subordinated agents and thus can match requests about what service/item can be offered by using which co-ordination mechanisms. To get the information about the co-ordination processes it stands in contact with its subordinated co-ordination mechanism agents (CMech). The co-ordination mechanism agents are a meta-control authority for all running, Fig. 2. The holonic co-ordination server and planned, co-ordination processes which are performed by so-called service providing co-ordination execution agents (CX).

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