research-article

Where to Place Your Next Restaurant?: Optimal Restaurant Placement via Leveraging User-Generated Reviews

Authors:

Weike PanAuthors Info & Claims

CIKM '16: Proceedings of the 25th ACM International on Conference on Information and Knowledge Management

Pages 2371 - 2376

https://doi.org/10.1145/2983323.2983696

Published: 24 October 2016 Publication History

Abstract

When opening a new restaurant, geographical placement is of prime importance in determining whether it will thrive. Although some methods have been developed to assess the attractiveness of candidate locations for a restaurant, the accuracy is limited as they mainly rely on traditional data sources, such as demographic studies or consumer surveys. With the advent of abundant user-generated restaurant reviews, there is a potential to leverage these reviews to gain some insights into users' preferences for restaurants. In this paper, we particularly take advantage of user-generated reviews to construct predictive features for assessing the attractiveness of candidate locations to expand a restaurant. Specifically, we investigate three types of features: review-based market attractiveness, review-based market competitiveness and geographic characteristics of a location under consideration for a prospective restaurant. We devise the three sets of features and incorporate them into a regression model to predict the number of check-ins that a prospective restaurant at a candidate location would be likely to attract. We then conduct an experiment with real-world restaurant data, which demonstrates the predictive power of features we constructed in this paper. Moreover, our experimental results suggest that market attractiveness and market competitiveness features mined solely from user-generated restaurant reviews are more predictive than geographic features.

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Cited By

Chang CJhang SYang YChang HChang Y(2024)Utilizing Skip-Gram for Restaurant Vector Creation and Its Application in the Selection of Ideal Restaurant LocationsSmart Grid and Internet of Things10.1007/978-3-031-55976-1_14(141-147)Online publication date: 15-Mar-2024
https://doi.org/10.1007/978-3-031-55976-1_14
Wang HLi HWang MCui J(2023)Toward Balancing the Efficiency and Effectiveness in k-Facility Relocation ProblemACM Transactions on Intelligent Systems and Technology10.1145/358703914:3(1-24)Online publication date: 13-Apr-2023
https://dl.acm.org/doi/10.1145/3587039
Hsieh HLai BChen YChang Y(2023)Multi-Performance Estimation for Deploying Bank Branches Based on a Multi-Task Attentive Tree-Enhanced ModelIEEE Transactions on Emerging Topics in Computational Intelligence10.1109/TETCI.2022.32145767:1(237-249)Online publication date: Feb-2023
https://doi.org/10.1109/TETCI.2022.3214576
Show More Cited By

Index Terms

Where to Place Your Next Restaurant?: Optimal Restaurant Placement via Leveraging User-Generated Reviews
1. Information systems
  1. Information systems applications
    1. Data mining

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cover image ACM Conferences

CIKM '16: Proceedings of the 25th ACM International on Conference on Information and Knowledge Management

October 2016

2566 pages

ISBN:9781450340731

DOI:10.1145/2983323

General Chairs:
Snehasis Mukhopadhyay
Indiana University Purdue University Indianapolis, USA
,
ChengXiang Zhai
University of Illinois at Urbana-Champaign, USA
,
Program Chairs:
Elisa Bertino
Purdue University
,
Fabio Crestani
University of Lugano
,
Javed Mostafa
University of North Carolina
,
Jie Tang
Tsinghua University
,
Luo Si
Alibaba Group Inc & Purdue University
,
Xiaofang Zhou
University of Queensland
,
Yi Chang
Yahoo Research
,
Yunyao Li
IBM Research - Almaden
,
Parikshit Sondhi
WalmartLabs

Copyright © 2016 ACM.

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Published: 24 October 2016

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October 24 - 28, 2016

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CIKM '16 Paper Acceptance Rate 160 of 701 submissions, 23%;

Overall Acceptance Rate 1,861 of 8,427 submissions, 22%

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Cited By

Chang CJhang SYang YChang HChang Y(2024)Utilizing Skip-Gram for Restaurant Vector Creation and Its Application in the Selection of Ideal Restaurant LocationsSmart Grid and Internet of Things10.1007/978-3-031-55976-1_14(141-147)Online publication date: 15-Mar-2024
https://doi.org/10.1007/978-3-031-55976-1_14
Wang HLi HWang MCui J(2023)Toward Balancing the Efficiency and Effectiveness in k-Facility Relocation ProblemACM Transactions on Intelligent Systems and Technology10.1145/358703914:3(1-24)Online publication date: 13-Apr-2023
https://dl.acm.org/doi/10.1145/3587039
Hsieh HLai BChen YChang Y(2023)Multi-Performance Estimation for Deploying Bank Branches Based on a Multi-Task Attentive Tree-Enhanced ModelIEEE Transactions on Emerging Topics in Computational Intelligence10.1109/TETCI.2022.32145767:1(237-249)Online publication date: Feb-2023
https://doi.org/10.1109/TETCI.2022.3214576
Kalra UKumar AHazra T(2022)Intelligent mobile vending services: location optimisation for food trucks using coalitional game theoryMultimedia Tools and Applications10.1007/s11042-022-13758-382:6(9477-9490)Online publication date: 16-Sep-2022
https://doi.org/10.1007/s11042-022-13758-3
Gao YHan DWang HZhang MHou FYu DXiong Y(2022)GeoGTI: Towards a General, Transferable and Interpretable Site RecommendationWeb Information Systems and Applications10.1007/978-3-031-20309-1_49(559-571)Online publication date: 16-Sep-2022
https://dl.acm.org/doi/10.1007/978-3-031-20309-1_49
Wang PChen WHuang JWei YFang JZhao L(2021)Location prediction for facility placement by incorporating multi-characteristic informationIntelligent Data Analysis10.3233/IDA-20542025:5(1187-1210)Online publication date: 15-Sep-2021
https://doi.org/10.3233/IDA-205420
Wang HLi HWang MCui JDemartini GZuccon GCulpepper JHuang ZTong H(2021)Addressing the Hardness of k-Facility Relocation ProblemProceedings of the 30th ACM International Conference on Information & Knowledge Management10.1145/3459637.3482411(1919-1928)Online publication date: 26-Oct-2021
https://dl.acm.org/doi/10.1145/3459637.3482411
Liu YGuo BZhang DZeghlache DChen JZhang SZhou DShi XYu Z(2021)MetaStore: A Task-adaptative Meta-learning Model for Optimal Store Placement with Multi-city Knowledge TransferACM Transactions on Intelligent Systems and Technology10.1145/344727112:3(1-23)Online publication date: 21-Apr-2021
https://dl.acm.org/doi/10.1145/3447271
Ahedo VSantos JGalan J(2021)Knowledge Transfer in Commercial Feature Extraction for the Retail Store Location ProblemIEEE Access10.1109/ACCESS.2021.31157129(132967-132979)Online publication date: 2021
https://doi.org/10.1109/ACCESS.2021.3115712
Alharthi KHindi KAlzahrani S(2021)Venue-Popularity Prediction Using Social Data Participatory Sensing Systems and RNNsIEEE Access10.1109/ACCESS.2020.30476809(3140-3154)Online publication date: 2021
https://doi.org/10.1109/ACCESS.2020.3047680
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