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Recommending Best Locations for New Restaurants

--IS Seminar Topic Analysis

Yingjie Zhang

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Introduction

• Location-based Data Network (LBSN)• Restaurants performance prediction

• Research Questions:• Extract and combine different geographical or mobility

features.• Detect causal effects of location-based features on restaurant

performance

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Literature Review

• Restaurant performances prediction• Location-based data usage• Features extraction (2 types)• Features combination (machine-learning-based techniques)• Data source (Foursquare check-ins dataset)

Model and Methods

• Features:• Static geographical features: • Dynamic consumer mobility features:• Restaurants specific features:

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Model and Methods

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• Step 1 Classification• Using to cluster locations with similar characteristics• Prepare for causal effects examinations

• Step 2 Prediction

Basic economic/behavior model using

Final prediction

model

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Data

• Online reservation system• Reservation availability information• Restaurant specific information

• Location-based service & Social media

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Challenges

• Choice of basic economic/behavior model• Modification of the basic economic model (or feature

combination)• Classification for the purpose of causal effect

examination

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Potential Implication

• Help business managers decide a new location• Help policy makers understand local economy• Help location-based service to improve their

performance

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Reference

• [1] Anderson, Michael, and Jeremy Magruder. "Learning from the crowd: Regression discontinuity estimates of the effects of an online review database*." The Economic Journal 122.563 (2012): 957-989.

• [2] Noulas, Anastasios, et al. "Mining user mobility features for next place prediction in location-based services." Data Mining (ICDM), 2012 IEEE 12th International Conference on. IEEE, 2012.

• [3] Karamshuk, Dmytro, et al. "Geo-Spotting: Mining Online Location-based Services for Optimal Retail Store Placement." arXiv preprint arXiv:1306.1704(2013).

• [4] Roick, Oliver, and Susanne Heuser. "Location Based Social Networks–Definition, Current State of the Art and Research Agenda." Transactions in GIS(2013).

• [5] Noulas, Anastasios, et al. "An Empirical Study of Geographic User Activity Patterns in Foursquare." ICWSM 11 (2011): 70-573.

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•Thanks!

•Q&A