Indoor Top-k Keyword-aware Routing Query

Zijin Feng, Tiantian Liu, Huan Li, Hua Lu, Lidan Shou, Jianliang Xu

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review


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 computing 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 languageEnglish
Title of host publicationThe 36th IEEE International Conference on Data Engineering (ICDE 2020) : Conference Proceedings
Place of PublicationUnited States
Publication date2020
ISBN (Electronic)978-1-7281-2903-7
Publication statusPublished - 2020
Externally publishedYes
Event36th IEEE International Conference on Data Engineering - Online, Dallas, United States
Duration: 20 Apr 202024 Apr 2020
Conference number: 36


Conference36th IEEE International Conference on Data Engineering
Country/TerritoryUnited States
OtherOnline conference
Internet address
SeriesProceedings of the International Conference on Data Engineering

Bibliographical note

35th IEEE International Conference on Data Engineering, ICDE 2019 ; Conference date: 08-04-2019 Through 11-04-2019


  • Indoor Query
  • Keyword-Aware Search
  • Routing Algorithm

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