Enhancing performance of keyword query over structured data

Keyword query applies to the database which accommodate structured data provide a search option over text attributes that uses a probability based ranking technique but query facing the issue of poor quality results. The keyword matches with multiple entities because the user does not provide exact data from which we can get better query results. Previous work analyze reasons behind the multiple answer and estimate the degree of difficulty for such tough query by using a ranking stability technique, but not addressed the problem of absent values under the attributes and it also imposes effectiveness problem of the query results. In this paper, we recognize and handle the issue of absent values by using both the inferring and retrieving based approaches. We evaluated our technique using real world data set and present performance advantages of our approach which improves the user satisfaction.

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