Efficient NFC Tagging Pattern-Based Contents Recommendation for Museum Viewers

Abstract:

As various ubiquitous computing technologies become applied into many smart space systems, most museums attempt to use these techniques for their own domain. Near Field Communication(NFC) is one of wireless technologies primarily used for short range communication between smart phones and similar devices, supporting a variety of information exchange services in some effective way. In this paper, we present a new user similarity-based contents recommendation service to improve the counterpart of our previously developed museum viewing system by using NFC. In order to satisfy this goal, this service utilizes similarity of artifact attached NFC tagging patterns of users. Its desirable feature enables users to actually find and obtain their favorite contents by systematically consulting the tastes of the other users very close to those of the first. Also, the proposed system may considerably reduce overloading on contents providing servers by having smart phone clients get certain parts of basic artifact related contents information directly through NFC tags, not the servers.

• Periodical: Applied Mechanics and Materials (Volumes 263-266)
• Pages: 2876-2880
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.263-266.2876
• Online since: December 2012
• Authors: Yoon Deuk Seo, Jin Ho Ahn
• Keywords: Contents Recommendation, Museum Viewing, NFC, Ubiquitous Sensor Network

References

[1] E. Schuman, NFC: A Technology Marvel That Must Overcome Human Psychology, Storefront Backtalk. www.storefrontbacktalk.com, 2008.

[2] NFC Forum, The Keys to Truly Interoperable Communications, www.nfcforum.org, 2007.

[3] Y. D. Seo, J. H. Ahn, Viewing Path Search and Congestion Control Algorithms For Comfortable Museum Viewing, KSII Trans. on Internet and Infor. Syst., 11, 3 (2010) 131-137.

[4] Y. D. Seo, J. H. Ahn, Comfortable and Effective Museum-Viewing System Providing Hybrid Contents Recommendation Service, Journal of Korean Institute of Information Technology, 9, 6 (2011) 121-129.

[5] S. J. Lee, S. W. Lee, A Comparison Study on Preference Calculate Methods for Content-Based Recommendation. Korea Information Science Society, 37, 2 (2010) 222-227.

[6] C. J. Park, Implementation and Performance Evaluation of a Hybrid Recommender System, Journal of Korean Institute of Information Technology, 6, 5 (2008) 217-224.

[7] J. G. Yim, J. H. Joo, S. H. Jeong, Wireless LAN-Based User Tracking Method and Experiment for Location-Based Services, Journal of Society for e-Business Studies, 13, 4 (2008) 1-16.

[8] D. Y. Kim, D. S. Seong, K. B. Lee, Implementation of an efficient multipoint sight-seeing guidance system based on LBS, Journal of Kor. Inst. of Info. Tech., 9, 1 (2011) 185-192.

[9] Y. D. Seo, J. H. Ahn, Reliable contents recommendation method based on social networking services, Proc. of the 2011 Korean Institute of Information Technology, 2011, pp.7-9.

[10] P. Ahlgren, B. Jarneving, R. Rousseau, Requirements for a cocitation similarity measure with special reference to Pearson's correlation coefficient, Journal of the American Society for Information Science and Technology, 54, 6 (2003) 550-560.

DOI: 10.1002/asi.10242