Massive amount of data that are geo-tagged and associated with text information are being generated at an unprecedented scale in many emerging applications such as location based services and social networks. Due to their importance, a large body of work has focused on efficiently computing various spatial keyword queries. In this paper,we study the top-k temporal spatial keyword query which considers three important constraints during the search including time, spatial proximity and textual relevance. A novel index structure, namely SSG-tree, to efficiently insert/delete spatio-temporal web objects with high rates. Base on SSG-tree an efficient algorithm is developed to support top-k temporal spatial keyword query. We show via extensive experimentation with real spatial databases that our method has increased performance over alternate techniques
@article{arxiv.1805.02009,
title = {Efficient Top K Temporal Spatial Keyword Search},
author = {Chengyuan Zhang and Lei Zhu and Weiren Yu and Jun Long and Fang Huang and Hongbo Zhao},
journal= {arXiv preprint arXiv:1805.02009},
year = {2018}
}