Open Access Open Access  Restricted Access Subscription or Fee Access

A Similarity Measures Algorithm for CBR Based on Matrix Iterative Learning

Lichcuan Gu, Zhiwei Ni, Zhang Jun Wu


With the rapid development of case-based reasoning (CBR) techniques such as case retrieval and case adaptation, CBR has been widely applied to various real-world applications. A successful case-based reasoning system requires a high-quality case base, which provides rich and efficient solutions for solving real-world problems. Similarity measure is not only the center part of Case-Based Reasoning systems, but also the key step of Case retrieval. In this paper, one algorithm is derived to learn the kernel matrix for capturing the relations between the case structure units based on matrix iterative analysis. For the performance evaluation, the proposed algorithm is applied to data of Pear Scab Forecasting-system. Comparing with the kernel matrix leaning algorithm based on the other methods, the experimental results show that the kernel matrix leaning algorithms based on matrix iterative analysis not only acquires higher precision but also needs less training documents and cost.


Case-based reasoning, Similarity measure, Matrix learning, Case retrieval.

Full Text:


Disclaimer/Regarding indexing issue:

We have provided the online access of all issues and papers to the indexing agencies (as given on journal web site). It’s depend on indexing agencies when, how and what manner they can index or not. Hence, we like to inform that on the basis of earlier indexing, we can’t predict the today or future indexing policy of third party (i.e. indexing agencies) as they have right to discontinue any journal at any time without prior information to the journal. So, please neither sends any question nor expects any answer from us on the behalf of third party i.e. indexing agencies.Hence, we will not issue any certificate or letter for indexing issue. Our role is just to provide the online access to them. So we do properly this and one can visit indexing agencies website to get the authentic information. Also: DOI is paid service which provided by a third party. We never mentioned that we go for this for our any journal. However, journal have no objection if author go directly for this paid DOI service.