Geo-Social Skyline Queries

Abstract

Abstract. By leveraging the capabilities of modern GPS-equipped mobile devices providing social-networking services, the interest in developing advanced services that combine location-based services with social networking services is growing drastically. Based on geo-social networks that couple personal location information with personal social context information, such services are facilitated by geo-social queries that extract useful information combining social relationships and current locations of the users. In this paper, we tackle the problem of geo-social skyline queries, a problem that has not been addressed so far. Given a set of persons D connected in a social network SN with information about their current location, a geo-social skyline query reports for a given user U ∈ D and a given location P (not necessarily the location of the user) the pareto-optimal set of persons who are close to P and closely connected to U in SN. We measure the social connectivity between users using the widely adoted, but very expensive Random Walk with Restart method (RWR) to obtain the social distance between users in the social network. We propose an efficient solution by showing how the RWR-distance can be bounded efficiently and effectively in order to identify true hits and true drops early. Our experimental evaluation shows that our presented pruning techniques allow to vastly reduce the number of objects for which a more exact social distance has to be computed, by using our proposed bounds only.

Geo-Social Top-k and Skyline Keyword Queries on Road Networks

“…They provided three approaches: social first, spatial first, and hybrid. The main difference between the GSSK query proposed in the current paper, and the problem studied by Emrich et al [8] and Sohail et al [9] is that the previous studies did not consider keyword relevance and their approaches were applied for Euclidean space. Wu et al [10] investigated a problem similar to the proposed GSTK query.…”

“…Emrich et al [8] introduced geo-social skyline queries that report the set of persons close to a given location, P and closely connected to user U. Sohail et al [9] recently introduced top-k famous places and socio-spatial skyline queries that consider social and spatial relevance to the query. They provided three approaches: social first, spatial first, and hybrid.…”

“…Geo-social queries [8][9][10] have recently attracted significant research attention due to their real-world relevance. Sohail et al [9] proposed a method to monitor socio-spatial top-k famous queries and skyline queries in Euclidean space.…”

Temporal Geo-Social Personalized Search Over Streaming Data

“…The unprecedented popularity of online social media platforms over the past decade combined with the availability of location information through GPS-equipped devices has led to significant attention for supporting geo-social queries at scale [5,6,13] in order to serve applications efficiently on such big data. These queries are used in various applications and services such as social recommendations [8,35,44], community and event detection [10,21,41], and urban planning [17].…”

“…This streaming nature has already motivated several streaming queries on this data, such as keyword queries [3,26,37], spatial queries [25,28], and social queries [23,30], with plenty of applications. Although several geo-social queries have been addressed in the literature [5,6,13,20,22,39,45], querying streaming data combining both social and geographic location information is still an unaddressed challenge.…”