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Urban treasure: new approach for collaborative local recommendation engine

Published: 29 October 2009 Publication History

Abstract

With human's infinite creativity, technology innovations are born in this world at an unprecedented rate. The rapid technology development has resulted in a fast-paced and complex life. Moreover, a dilemma is posed as people tend to fall into confusion when they are suddenly withdrawn from their occupied daily routine: our knowledge about our own community, besides our working environment, is limited due to our lack of both motivation and time for local exploration. How to increase and enhance people's appreciation for their daily surroundings then becomes the fundamental vision of Urban Treasure: a collaborative local recommendation engine which allows users to discover new local information that match their personal preferences.

Reference

[1]
Minnano DOCOMO Kenkyu-Shitsu http://trial.nttdocomo.co.jp/technology/ar/index.html.

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  1. Urban treasure: new approach for collaborative local recommendation engine

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    ACE '09: Proceedings of the International Conference on Advances in Computer Entertainment Technology
    October 2009
    456 pages
    ISBN:9781605588643
    DOI:10.1145/1690388
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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    Association for Computing Machinery

    New York, NY, United States

    Publication History

    Published: 29 October 2009

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    Author Tags

    1. location
    2. mobile entertainment
    3. recommendation technology
    4. social networks
    5. user interface

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    ACE '09
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    Overall Acceptance Rate 36 of 90 submissions, 40%

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