Abstract
A reverse top-k keyword-based location query returns the influence zone for the query object. Given a specified query object q, the influence zone of q varies for different key-word sets. Users may be interested in identifying the maximum influence zone of the query object. To this end, we study the problem called MaxiZone that finds the keyword set maximizing the influence zone of a specified query object. The MaxiZone problem has many real-life applications, e.g., a business owner would like to identify the maximum influence zone so as to attract as many customers as possible. To address the MaxiZone problem, we propose three algorithms, including a basic algorithm, an index-centric algorithm together with a series of optimizations and a sampling-based algorithm. Extensive empirical study using real-world datasets demonstrates the effectiveness and efficiency of proposed algorithms.
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