Remarks on a Fuzzy Approach to Flexible Database Querying, Its Extension and Relation to Data Mining and Summarization

For an effective and efficient information search of databases, various issues should be solved. A very important one, though still usually neglected by traditional database management systems, is related to a proper representation of user preferences and intentions, and then their representation in querying languages. In many scenarios, they are not clear-cut, and often have their original form deeply rooted in natural language implying a need of flexible querying. Although the research on introducing elements of natural language into the database querying languages dates back to the late 1970s, the practical commercial solutions are still not widely available. This chapter is meant to revive the line of research in flexible querying languages based on the use of fuzzy logic. This chapter recalls details of a basic technique of flexible fuzzy querying, discusses some newest developments in this area and, moreover, shows how other relevant tasks may be implemented in the framework of such queries interface. In particular, it considers fuzzy queries with linguistic quantifiers and shows their intrinsic relation with linguistic data summarization. Moreover, the chapter mentions so called “bipolar queries” and advocates them as a next relevant breakthrough in flexible querying based on fuzzy logic and possibility theory.