An Adaptive Query Relaxation Approach for Relational Databases Based on Semantic Similarity
Meng Xiang · Chinese Journal of Computers · 2011
To deal with the problem of empty answers of the relational database,an adaptive query relaxation approach,which is based on semantic similarity,is proposed.Firstly,according to the query conditions and data distribution the importance of each specified attribute for the user is speculated,and then an attribute weight measuring method is proposed.Next,based on the properties of attribute values,the semantic similarity measuring method of categorical attribute value(resp.numerical attribute value) is proposed.According to the relaxation threshold,attribute weights and semantic similarities of attribute values,an adaptive query relaxation rewriting algorithm is proposed.The tuples satisfying the relaxed query are finally ranked according to their satisfaction degree.Results of experiments demonstrate that the performance and results of attribute weight and attribute values similarity measuring methods proposed are stable and reasonable respectively,the query relaxation method proposed has higher recall and can capture the user's needs and preferences effectively as well.