A common issue with case-based reasoning (CBR) systems, particularly those that are distributed over a network, is the time required to determine the closest match to the current case. Research has been carried out in this area to try to improve the situation by distributing some of the calculation to the client side thereby reducing the burden on the server. In CBR applications, the case library is stored in some format such as a relational database or flat files that the software interprets in order to perform similarity assessment between the current case and each case in the database. In this paper a novel approach is proposed where the retrieval of the case information and the calculation of the similarity values are performed in one action. This does not incur the same burden upon the server in terms of calculation, as all that is required is a larger database lookup via SQL. As the case base needs to be queried regardless of the CBR technique used to obtain the case information, it is proposed that a combined similarity assessment and case retrieval would provide a fast method of case retrieval.
|LECTURE NOTES IN ARTIFICIAL INTELLIGENCE
|5th International Conference on Case-Bases Reasoning (ICCBR 2003)
|23/06/03 → 26/06/03
- computer science
- artificial intelligence