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AR-HITOKE: visualizing popularity of brick and mortar shops to support purchase decisions

Published:09 March 2015Publication History

ABSTRACT

We propose a shopping support system (AR-HITOKE) that visualizes the popularity of brick and mortar shops by aggregating online and offline information using augmented reality technology that can be understood intuitively. In the proposed method, 3D-animated human-shaped icons in queues and user comments are overlaid above a shop's location on a physical map. Popularity is expressed visually by adjusting the queues length depending on offline sales data. We also visualize user comments related to each shop that are extracted from online reviews using our sentiment analysis framework. The proposed method offers new evaluation information for decision making in a physical environment and new online shopping experiences. Through exhibition of the proposed system at an actual event, we found that users are able to recognize the popularity of shops intuitively.

References

  1. Raymond A. Bauer, Consumer Behavior as Risk Taking. In Dynamic Marketing for a Changing World, Robert S. Hancock, ed. (Chicago: American Marketing Assn., 1960), pp. 389--398 (1960).Google ScholarGoogle Scholar
  2. Masuko, S. and Abe H., HITOKE: A study of queue visualization of internet purchase information. In Proc. CHI 2013, ACM Press, 1839--1844 (2013). Google ScholarGoogle ScholarDigital LibraryDigital Library
  3. Zhu, W., et al., Personalized In-store E-Commerce with the PromoPad: an Augmented Reality Shopping Assistant. The Electronic Journal for E-Commerce Tools & Applications, 2004. 1 (3).Google ScholarGoogle Scholar

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  1. AR-HITOKE: visualizing popularity of brick and mortar shops to support purchase decisions

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      • Published in

        cover image ACM Other conferences
        AH '15: Proceedings of the 6th Augmented Human International Conference
        March 2015
        241 pages
        ISBN:9781450333498
        DOI:10.1145/2735711
        • General Chairs:
        • Suranga Nanayakkara,
        • Ellen Yi-Luen Do,
        • Program Chairs:
        • Jun Rekimoto,
        • Jochen Huber,
        • Bing-Yu Chen

        Copyright © 2015 ACM

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        Association for Computing Machinery

        New York, NY, United States

        Publication History

        • Published: 9 March 2015

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        Acceptance Rates

        Overall Acceptance Rate121of306submissions,40%

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