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- W3204301116 abstract "In this paper, we study a novel variant of geo-social group queries, namely, keyword-based geo-social group (KGSG) queries. Motivated by group-based activity planning, KGSG ensures that the attendees have a good social relationship, are close enough to the activity location, and are interested in the activity. Efficient processing of the KGSG query is very challenging as the problem is NP-hard. To address the challenge, we first propose two R-tree based algorithms, namely Distance Ordering based (Baseline) and Breadth Distance Ordering with Neighbor Expanding (BDONE). To further improve these two R-tree based algorithms, we propose a new keyword-aware social spatial index, called SIR-tree, which incorporates spatial, social and keyword information into an R-tree. The novelty of SIR-tree lies in the idea of projecting the social relationships of an LBSN on the spatial layer which also maintains the users keyword information, to facilitate efficient KGSG query processing. Accordingly, we develop an efficient algorithm, called KGSG by SIR-tree Acceleration (KGSG-SIR), which exploits SIR-tree to accelerate query processing of KGSG. We conduct an extensive performance evaluation using four real datasets to validate our ideas and the proposed algorithms. The experimental result shows that the KGSG-SIR algorithm outperforms the two algorithms significantly." @default.
- W3204301116 created "2021-10-11" @default.
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- W3204301116 date "2021-01-01" @default.
- W3204301116 modified "2023-10-18" @default.
- W3204301116 title "Towards Keyword-based Geo-Social Group Query Services" @default.
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- W3204301116 doi "https://doi.org/10.1109/tsc.2021.3115132" @default.
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