Abstract
People have many activities indoors and there is an increasing demand of keyword-aware route planning for indoor venues. In this paper, we study the indoor top-k keyword-aware routing query (IKRQ). Given two indoor points s and t, an IKRQ returns k s-to-t routes that do not exceed a given distance constraint but have optimal ranking scores integrating keyword relevance and spatial distance. It is challenging to efficiently compute the ranking scores and find the best yet diverse routes in a large indoor space with complex topology. We propose prime routes to diversify top-k routes, devise mapping structures to organize indoor keywords and compute route keyword relevances, and derive pruning rules to reduce search space in routing. With these techniques, we design two search algorithms with different routing expansions. Experiments on synthetic and real data demonstrate the efficiency of our proposals.
Original language | English |
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Title of host publication | Proceedings - 2020 IEEE 36th International Conference on Data Engineering, ICDE 2020 |
Publisher | IEEE Computer Society |
Pages | 1213-1224 |
Number of pages | 12 |
ISBN (Electronic) | 9781728129037 |
DOIs | |
Publication status | Published - Apr 2020 |
Event | 36th IEEE International Conference on Data Engineering, ICDE 2020 - Dallas, United States Duration: 20 Apr 2020 → 24 Apr 2020 https://ieeexplore.ieee.org/xpl/conhome/9093725/proceeding (Link to conference proceedings) |
Publication series
Name | Proceedings - International Conference on Data Engineering |
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Volume | 2020-April |
ISSN (Print) | 1084-4627 |
Conference
Conference | 36th IEEE International Conference on Data Engineering, ICDE 2020 |
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Country/Territory | United States |
City | Dallas |
Period | 20/04/20 → 24/04/20 |
Internet address |
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Scopus Subject Areas
- Software
- Signal Processing
- Information Systems