A Novel Approach for User and Query-Dependent Ranking for Web Databases

Computer Engineering

Query dependent ranking has become a routine task as the requirement of searching the various values of web database has grown. Requirement of searching electronic product, car, real estate and other products has emerged with the hike of internet use. Earlier approach for addressing this problem have used frequencies for database values, query log and user profile. A common thread in most of this approach is that ranking is done in a user- and/or query– independent manner. Our research has focused on user and query dependent approach for getting the result from various datasets. Here, a query dependent ranking model is presented where functionalities related to workload depends on the several ranking strategies like KD- Tree, K-Mean or K-NN algorithm. We demonstrate a comparative studies of result with similar queries. We defined a similarity formally in alternative ways to discuss the effectiveness analytically and experimentally over two district database.

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