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An Efficient Algorithm for Location-Aware Query Autocompletion
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Summary :
Query autocompletion is an important and practical technique when users want to search for desirable information. As mobile devices become more and more popular, one of the main applications is location-aware service, such as Web mapping. In this paper, we propose a new solution to location-aware query autocompletion. We devise a trie-based index structure and integrate spatial information into trie nodes. Our method is able to answer both range and top-k queries. In addition, we discuss the extension of our method to support the error tolerant feature in case user's queries contain typographical errors. Experiments on real datasets show that the proposed method outperforms existing methods in terms of query processing performance.
- Publication
- IEICE TRANSACTIONS on Information Vol.E101-D No.1 pp.181-192
- Publication Date
- 2018/01/01
- Publicized
- 2017/10/05
- Online ISSN
- 1745-1361
- DOI
- 10.1587/transinf.2017EDP7152
- Type of Manuscript
- PAPER
- Category
- Data Engineering, Web Information Systems
Authors
Sheng HU
Nagoya University
Chuan XIAO
Nagoya University
Yoshiharu ISHIKAWA
Nagoya University
Keyword
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Sheng HU, Chuan XIAO, Yoshiharu ISHIKAWA, "An Efficient Algorithm for Location-Aware Query Autocompletion" in IEICE TRANSACTIONS on Information,
vol. E101-D, no. 1, pp. 181-192, January 2018, doi: 10.1587/transinf.2017EDP7152.
Abstract: Query autocompletion is an important and practical technique when users want to search for desirable information. As mobile devices become more and more popular, one of the main applications is location-aware service, such as Web mapping. In this paper, we propose a new solution to location-aware query autocompletion. We devise a trie-based index structure and integrate spatial information into trie nodes. Our method is able to answer both range and top-k queries. In addition, we discuss the extension of our method to support the error tolerant feature in case user's queries contain typographical errors. Experiments on real datasets show that the proposed method outperforms existing methods in terms of query processing performance.
URL: https://global.ieice.org/en_transactions/information/10.1587/transinf.2017EDP7152/_p
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@ARTICLE{e101-d_1_181,
author={Sheng HU, Chuan XIAO, Yoshiharu ISHIKAWA, },
journal={IEICE TRANSACTIONS on Information},
title={An Efficient Algorithm for Location-Aware Query Autocompletion},
year={2018},
volume={E101-D},
number={1},
pages={181-192},
abstract={Query autocompletion is an important and practical technique when users want to search for desirable information. As mobile devices become more and more popular, one of the main applications is location-aware service, such as Web mapping. In this paper, we propose a new solution to location-aware query autocompletion. We devise a trie-based index structure and integrate spatial information into trie nodes. Our method is able to answer both range and top-k queries. In addition, we discuss the extension of our method to support the error tolerant feature in case user's queries contain typographical errors. Experiments on real datasets show that the proposed method outperforms existing methods in terms of query processing performance.},
keywords={},
doi={10.1587/transinf.2017EDP7152},
ISSN={1745-1361},
month={January},}
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TY - JOUR
TI - An Efficient Algorithm for Location-Aware Query Autocompletion
T2 - IEICE TRANSACTIONS on Information
SP - 181
EP - 192
AU - Sheng HU
AU - Chuan XIAO
AU - Yoshiharu ISHIKAWA
PY - 2018
DO - 10.1587/transinf.2017EDP7152
JO - IEICE TRANSACTIONS on Information
SN - 1745-1361
VL - E101-D
IS - 1
JA - IEICE TRANSACTIONS on Information
Y1 - January 2018
AB - Query autocompletion is an important and practical technique when users want to search for desirable information. As mobile devices become more and more popular, one of the main applications is location-aware service, such as Web mapping. In this paper, we propose a new solution to location-aware query autocompletion. We devise a trie-based index structure and integrate spatial information into trie nodes. Our method is able to answer both range and top-k queries. In addition, we discuss the extension of our method to support the error tolerant feature in case user's queries contain typographical errors. Experiments on real datasets show that the proposed method outperforms existing methods in terms of query processing performance.
ER -
English
