ADAPTING QUERY REPRESENTATION TO IMPROVE RETRIEVAL IN A FUZZY DATABASE
Jorge Gasós, Anca Ralescu · International Journal of Uncertainty Fuzziness and Knowledge-Based Systems · 1995
We present an adjustment-to-user facility of a facial images database system in order to improve retrieval performance. The system uses linguistic (qualitative) descriptions, both in the data model and in the query language. These descriptions are internally represented as fuzzy sets. As the same linguistic descriptions can be used by different users to describe different values, the need of adjusting fuzzy sets, such that the user’s meaning is represented arises. We provide a method which, upon repeated queries by the same user, finds the best representation (as fuzzy set) of the linguistic descriptions given by the user in question. The method is based on an extension of the inverse problem of matching of fuzzy sets. Experiments show that when compared with the unadjusted system, significantly better results are obtained during the process of finding the best representation, and much better results after the best representation (given the whole database) is found.