PAPER ON BEST KEYWORD COVER SEARCH USING QUERY PROCESSING

Computer Engineering

It is very common that the objects in a structural database (e.g., restaurants/hotels) are linked with keyword(s) to show their businesses/services/features. An interesting problem called as Closest Keywords search is to query objects, called keyword cover, which together cover a set of query keywords and have the minimum inter-objects distance. In recent few years, we observe the increasing availability and importance of keyword rating in object evaluation for the better decision making. This motivates and show us to detailed investigate a generic version of Closest Keywords search called Best Keyword Cover search which considers inter-objects distance as well as the keyword rating of objects. The baseline algorithm is I truly inspired by the methods of Closest Keywords search which is based on exhaustively combining objects from different query keywords to generate and indicate candidate keyword covers. When the number of query keywords increases rapidly, the performance of the baseline algorithm drops dramatically as a result of massive candidate keyword covers generated. To attack this drawback, this work proposes a much more scalable algorithm called keyword nearest neighbour expansion (keyword-NNE). Compared to the base line algorithm, keyword-NNE algorithm significantly reduces the number of candidate keyword covers generated. The in-depth analysis and extensive experiments on real data sets have justified the superiority of our keyword-NNE algorithm.

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