Download Case-Based Reasoning Research and Development: 19th by Kristian J. Hammond (auth.), Ashwin Ram, Nirmalie Wiratunga PDF

By Kristian J. Hammond (auth.), Ashwin Ram, Nirmalie Wiratunga (eds.)

This publication constitutes the refereed court cases of the nineteenth overseas convention on Case-Based Reasoning, held in London, united kingdom, in September 2011.
The 32 contributions awarded including three invited talks have been rigorously reviewd and chosen from sixty seven submissions. The displays and posters lined a variety of CBR subject matters of curiosity either to practitioners and researchers, together with CBR technique protecting case illustration, similarity, retrieval, and model; provenance and upkeep; recommender platforms; multi-agent collaborative structures; information mining; time sequence research; net functions; wisdom administration; felony reasoning; healthcare structures and making plans systems.

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Extra resources for Case-Based Reasoning Research and Development: 19th International Conference on Case-Based Reasoning, ICCBR 2011, London, UK, September 12-15, 2011. Proceedings

Sample text

As baseline for the comparison, we computed the similarity by a lexical similarity measure, in particular a Levenshtein similarity measure on the task and data names. Besides this, the same functions FE and FW were used. For both similarity measures, we compared the ordering of the cases with those of the human expert. As a measure of correctness we used the ranking measure proposed by Cheng et al. e. by the number of case pairs for which both orders differ. Correctness and completeness are defined as follows: Corr = (C − D)/(C + D) and Compl = C/| ∗ |.

The similarity value for the mapping assesses the utility of this reuse opportunity. For a case there are usually several mappings that reflect different ways of reusing the case. e the mapping with the highest similarity: sim(QW, CW ) = max{simm (QW, CW )| mapping m}. To summarize, the presented similarity model for workflows is defined by three model parameters, 1st the similarity function simΣ for semantic descriptions, 2nd the aggregation function for edges FE , and 3rd the aggregation function for workflows FW .

Search terminates, when at least k searches have terminated and when the similarity of the k-best case is higher than all f values of the remaining queues. Since the f -values are upper bounds for the final similarity, it is ensured that none of the remaining cases can ever exceed the similarity of the known k-best case. Hence, completeness of k-best retrieval is guaranteed. The following algorithm returns the list of the k-best cases (and possibly some more) together with its similarity value. A*P Retrieval (QW = (Nq , Eq , Tq , Sq ), CB = {CW1 , .

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