Efficient Top K Temporal Spatial Keyword Search
Chengyuan Zhang, Lei Zhu, Weiren Yu, Jun Long, Fang Huang, Hongbo Zhao

TL;DR
This paper introduces SSG-tree, a novel index structure that efficiently supports top-k temporal spatial keyword queries considering time, location, and relevance, demonstrated to outperform existing methods.
Contribution
The paper presents the SSG-tree index and an efficient algorithm for top-k temporal spatial keyword search, addressing high-rate data updates and query performance.
Findings
SSG-tree significantly improves query response times.
The method outperforms alternative techniques in real spatial database experiments.
Efficiently handles high-frequency insertions and deletions.
Abstract
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- 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
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Taxonomy
TopicsData Management and Algorithms · Advanced Database Systems and Queries · Geographic Information Systems Studies
