A hypothesis refinement method for summary discovery in databases

Abstract

As database systems are playing major roles in more and more applications, the amount of information in databases is rapidly growing. In order to comprehend those large volumes of information, computerized summary discovery methods are required. In this paper, we propose a hypothesis refinement method for constructing and evaluating fuzzy hypotheses. Breed on them we propose an effective and robust algorithm to discover simple linguistic summaries. In addition, we present ideas for exploiting discovered summaries to various applications such as querying database knowledge, handling query failures and semantic query optimization.