A Recommendation Service Model in Copyright Management Portal System for National Research Reports
Pages 144 - 147
Abstract
To manage the copyrights of national research reports in Korea, a copyright management portal system is designed and is developing. In the portal system, recommendation service becomes an essential component to serve convenience to users. However, it is hard to develop recommendation service for research reports in the portal differently from other fields, because it is difficult to collect the dynamic information of users and national research reports. In this paper, we suggest improved recommendation service model which uses the log records of user against research reports in copyright management portal system. In result of questionnaire for 50 graduate students, the accuracy of recommended papers seems to be satisfied widely. Also, they answered it is expected that this recommendation service will save the amount of time they have spent researching by half.
References
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Kim, S., 2014, The rank of R&D dept. asset in South Korea is top among OECD countries, Asia times, http://www.asiatime.co.kr/news/articleView.html?idxno=71120 {Online}
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Son, J., Kim, S., Kim, H. and Cho, S., 2015. Review and Analysis of Recommender Systems, Journal of the Korean Institute of Industrial Engineers, 41, 2(Apr.2015), 185--208
[3]
Yeo, W.D., Park, H.W., Kwon, Y.I. and Park, Y.W., 2010. Application of Research Paper Recommender System to Digital Library, The journal of Korea content association, 10, 11(2010), 10--19
[4]
Song, K., Min, J., and Kim, Y.S., 2015, A Copyright Management Service Model for National Research Reports in Korea, Proceeding of The Second International Conference On Advances in Computing, Control And Networking(Bangkok, Thailand, Aug 28-29, 2015). ACCN 2015, 106--110
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Wikipedia https://en.wikipedia.org/wiki/Recommender_system#Content-based_filtering {Online}
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Lee, S.G., Lee, B.S., Bak, B.Y and Hwang, H.K., 2010. A Study of Intelligent Recommendation System based on Naïve Bayes Text Classification and Collaborative Filtering, Journal of information management, 41, 4(2010), 227--249
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Wikipedia https://en.wikipedia.org/wiki/Recommender_system#Collaborative_filtering {Online}
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Information & Contributors
Information
Published In
October 2015
321 pages
ISBN:9781450338462
DOI:10.1145/2837060
- Conference Chairs:
- Jongsup Choi,
- Sun Hwa Han,
- Joo-Yeoun Lee,
- Taeho Park,
- Editor:
- Aziz Nasridinov,
- Program Chairs:
- Carson K. Leung,
- Yoo-Sung Kim,
- Young-Koo Lee
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Association for Computing Machinery
New York, NY, United States
Publication History
Published: 20 October 2015
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- Research
- Refereed limited
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BigDAS '15
BigDAS '15: 2015 International Conference on Big Data Applications and Services
October 20 - 23, 2015
Jeju Island, Republic of Korea
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