Answering Why-Not Group Spatial Keyword Queries (Extended Abstract)

Bolong Zheng, Kai Zheng, Christian S. Jensen, Nguyen Quoc Viet Hung, Han Su, Guohui Li, Xiaofang Zhou

Research output: Contribution to book/anthology/report/conference proceedingArticle in proceedingResearchpeer-review

1 Citation (Scopus)

Abstract

With the proliferation of geo-textual objects on the web, extensive efforts have been devoted to improving the efficiency of top-k spatial keyword queries in different settings. However, comparatively much less work has been reported on enhancing the quality and usability of such queries. In this context, we propose means of enhancing the usability of a top-k group spatial keyword query, where a group of users aim to find k objects that contain given query keywords and are nearest to the users. Specifically, when users receive the result of such a query, they may find that one or more objects that they expect to be in the result are in fact missing, and they may wonder why. To address this situation, we develop a so-called why-not query that is able to minimally modify the original query into a query that returns the expected, but missing, objects, in addition to other objects. Specifically, we formalize the why-not query in relation to the top-k group spatial keyword query, called the Why-not Group Spatial Keyword Query (WGSK) that is able to provide a group of users with a more satisfactory query result. We propose a three-phase framework for efficiently computing he WGSK. Extensive experiments with real and synthetic data offer evidence that the proposed solution excels over baselines with respect to both effectiveness and efficiency.
Original languageEnglish
Title of host publicationProceedings - 2019 IEEE 35th International Conference on Data Engineering, ICDE 2019
Number of pages2
PublisherIEEE
Publication date2019
Pages2155-2156
Article number8731602
ISBN (Print)978-1-5386-7475-8
ISBN (Electronic)978-1-5386-7474-1
DOIs
Publication statusPublished - 2019
Event35th IEEE International Conference on Data Engineering, ICDE 2019 - Macau, China
Duration: 8 Apr 201911 Apr 2019

Conference

Conference35th IEEE International Conference on Data Engineering, ICDE 2019
Country/TerritoryChina
CityMacau
Period08/04/201911/04/2019
SeriesProceedings of the International Conference on Data Engineering
ISSN1063-6382

Keywords

  • Query processing
  • Spatial keyword queries
  • Top k query
  • Why not

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