Interactive top-k spatial keyword queries

Zheng, Kai, Su, Han, Zheng, Bolong, Shang, Shuo, Xu, Jiajie, Liu, Jiajun and Zhou, Xiaofang (2015). Interactive top-k spatial keyword queries. In: 2015 IEEE 31st International Conference on Data Engineering, ICDE 2015. IEEE International Conference on Data Engineering, Seoul, South Korea, (423-434). 13-17 April 2015. doi:10.1109/ICDE.2015.7113303


Author Zheng, Kai
Su, Han
Zheng, Bolong
Shang, Shuo
Xu, Jiajie
Liu, Jiajun
Zhou, Xiaofang
Title of paper Interactive top-k spatial keyword queries
Conference name IEEE International Conference on Data Engineering
Conference location Seoul, South Korea
Conference dates 13-17 April 2015
Convener IEEE
Proceedings title 2015 IEEE 31st International Conference on Data Engineering, ICDE 2015   Check publisher's open access policy
Journal name Proceedings - International Conference on Data Engineering   Check publisher's open access policy
Place of Publication Piscataway, NJ, United States
Publisher IEEE
Publication Year 2015
Sub-type Fully published paper
DOI 10.1109/ICDE.2015.7113303
Open Access Status Not Open Access
ISBN 9781479979639
9781479979646
ISSN 1084-4627
Volume 2015-May
Start page 423
End page 434
Total pages 12
Collection year 2016
Abstract/Summary Conventional top-k spatial keyword queries require users to explicitly specify their preferences between spatial proximity and keyword relevance. In this work we investigate how to eliminate this requirement by enhancing the conventional queries with interaction, resulting in Interactive Top-k Spatial Keyword (ITkSK) query. Having confirmed the feasibility by theoretical analysis, we propose a three-phase solution focusing on both effectiveness and efficiency. The first phase substantially narrows down the search space for subsequent phases by efficiently retrieving a set of geo-textual k-skyband objects as the initial candidates. In the second phase three practical strategies for selecting a subset of candidates are developed with the aim of maximizing the expected benefit for learning user preferences at each round of interaction. Finally we discuss how to determine the termination condition automatically and estimate the preference based on the user's feedback. Empirical study based on real PoI datasets verifies our theoretical observation that the quality of top-k results in spatial keyword queries can be greatly improved through only a few rounds of interactions.
Subjects 1710 Information Systems
1711 Signal Processing
1712 Software
Q-Index Code E1
Q-Index Status Confirmed Code
Institutional Status UQ

 
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