Reverse nearest neighbourhood query based on road social networks

With the increasing popularity of mobile devices that support spatial position-ing, numerous location-based service LBS systems have been put into place and widely adopted by users of mobile devices. Reverse nearest neighbor RNN queries are essential supporting techniques in these systems. A new and useful variant of RNN queries has emerged recently, known as reverse nearest neighbourhood concept for road networks RNNH-RN , to discover the neigh-bourhood that finds the query point is the nearest facilities among all other fa-cilities. However, existing research has primarily focused on spatial queries, and to the best of our knowledge, there is no technique available for computing queries that incorporate social network information. The questions people cur-rently ask about road networks are not applicable to road social networks di-rectly. In this paper, we introduce the reverse nearest neighbourhood query based on road social networks RNNH-RS , where a neighbourhood is a set of at least m objects, ensuring that the maximum road network distance between any objects is at most d, and the objects within the neighbourhood have at least k, familiar acquaintances. We validated the flexibility and effectiveness of the proposed query through experiments on a real-world road social network da-taset.