Research Article
MCOPS-SPM: Multi-Constrained Optimized Path Selection Based Spatial Pattern Matching in Social Networks
@INPROCEEDINGS{10.1007/978-3-030-48513-9_1, author={Ying Guo and Lianzhen Zheng and Yuhan Zhang and Guanfeng Liu}, title={MCOPS-SPM: Multi-Constrained Optimized Path Selection Based Spatial Pattern Matching in Social Networks}, proceedings={Cloud Computing, Smart Grid and Innovative Frontiers in Telecommunications. 9th EAI International Conference, CloudComp 2019, and 4th EAI International Conference, SmartGIFT 2019, Beijing, China, December 4-5, 2019, and December 21-22, 2019}, proceedings_a={CLOUDCOMP}, year={2020}, month={6}, keywords={Location-Based Social Network Multiple constraints Optimized path selection Spatial Pattern Matching}, doi={10.1007/978-3-030-48513-9_1} }- Ying Guo
Lianzhen Zheng
Yuhan Zhang
Guanfeng Liu
Year: 2020
MCOPS-SPM: Multi-Constrained Optimized Path Selection Based Spatial Pattern Matching in Social Networks
CLOUDCOMP
Springer
DOI: 10.1007/978-3-030-48513-9_1
Abstract
In this paper, we study the multi-constrained optimized path selection based spatial pattern matching in Location-Based Social Network (MCOPS-SPM). Given a set D including spatial objects (each with a social identity and a social reputation) and social relationships (e.g., trust degree, social intimacy) between them. We aim at finding all connections (paths) of objects from D that match a user-specified multi-constraints spatial pattern P. A pattern P is a complex network where vertices represent spatial objects, and edges denote social relationships between them. The MCOPS-SPM query returns all the instances that satisfy P. Answering such queries is computationally intractable, and we propose algorithms to solve the multi-constrained optimized path matching problem and guide the join order of the paths in the query results. An extensive empirical study over real-world datasets has demonstrated the effectiveness and efficiency of our approach.
