Estimation of Potential Product Using Reverse Top-k Queries

Atpresent, most of the applications return to the user a limited set of ranked results based on the individual user’s preferences, which are commonly validated through top-k queries. From the perspective of a manufacturer, it is imperative that the products appear in the highest ranked positions for many different user preferences, otherwise the product is not visible to the potential customers. In this paper, I define a novel query type, namely the reverse top-k query, that covers the requirement of potential product, which are the user preferences that make this product belong to the top-k query result set. Reverse top-k queries are essential for manufacturers to assess the impact of their products in the market based on the competition. I formally define reverse top-k queries and introduce two versions of the query, monochromatic and bichromatic. First, I provide a geometric interpretation of the monochromatic reverse top-k query to acquire an intuition of the solution space. Then, I study in detail the case of bichromatic reverse top-k query, and I propose two techniques for query processing, namely an efficient threshold-based algorithm and an algorithm based on materialized reverse top-k views. My experimental evaluation demonstrates the efficiency of the reverese Top-K Queries.