Fuzzy query results ranking over autonomous web databases

Users often have vague or imprecise ideas when searching the Web database, thus they might like to issue fuzzy queries that consist of fuzzy terms or fuzzy relations for possibly retrieving. To deal with the problem of too many results returned from a Web database in response to a user fuzzy query, this paper proposes a novel approach to rank the fuzzy query results. Based on database workload, we firstly speculate the importance of each attribute and assign a corresponding weight to it. And then, based on fuzzy sets theory, a membership degree ranking method, which ranks the query results according to the tuple´s satisfaction degree to the fuzzy query, is presented. Next, based on data and workload statistics and correlations, we present a relevance degree ranking method, which assigns a relevance score for each unspecified attribute value according to its corresponding attribute weight and its desirableness to the user. Results of preliminary experiments demonstrating the efficiency and efficacy of the ranking approach are presented.