Personalization of LBS using Recommender Systems Based on Collaborative Filtering

Hyeong-Joon Kwon; Kwang-Seok Hong

Personalization of LBS using Recommender Systems Based on Collaborative Filtering

Hyeong-Joon Kwon, Kwang-Seok Hong, Journal of Internet Computing and Services, Vol. 11, No. 6, pp. 1-12, Dec. 2010
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Abstract

While a supply of GPS-enabled smartphone is increased, LBS which is studied and developed for special function is changed to personal solution. In this paper, we propose and implement on personalized method of individual LBS using collaborative filtering-based recommend system. Proposed personalized LBS system recommends contents which is expected to be interest for individual user, by predicting location-based contents within a user's setting radius. To evaluate performance of proposed system, we observed prediction accuracy with various experimental condition using our prototype. As a result, we confirmed that the convergence of collaborative filtering and LBS is effective for personalized LBS.

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Cite this article

[APA Style]

Kwon, H. & Hong, K. (2010). Personalization of LBS using Recommender Systems Based on Collaborative Filtering. Journal of Internet Computing and Services, 11(6), 1-12.

[IEEE Style]

H. Kwon and K. Hong, "Personalization of LBS using Recommender Systems Based on Collaborative Filtering," Journal of Internet Computing and Services, vol. 11, no. 6, pp. 1-12, 2010.

[ACM Style]

Hyeong-Joon Kwon and Kwang-Seok Hong. 2010. Personalization of LBS using Recommender Systems Based on Collaborative Filtering. Journal of Internet Computing and Services, 11, 6, (2010), 1-12.