Professor Shinsuke Nakajima

Area and Subject Taught Social Computing
Research Theme(s) (1) Recommender system by considering users’ context
(2) Extraction of collective intelligence based on web mining
Academic Degrees Ph.D., Kyoto University
Keywords for Research Field Information Retrieval, Recommender System, Web Mining, Blog Mining
Office Phone Number Not Public
e-mail

Research Overview

With the spread of computers and the internet, the amount of information that can be obtained is increasing and the technology to process the information is becoming increasingly advanced. However, for the general end-user, this advanced informationprocessing technology must be technology that does not complicate the utilization of information and must be easy and useful to use technology. With the aim of realizing an information system in which the general end-user can simply and conveniently utilize information without being aware of the advanced information-processing going on behind the scenes, I am carrying out research and development with a particular focus on recommender system and web mining.

Notable Publications and Works in the Last Three Years

  1. Jianwei Zhang, Seiya Tomonaga, Shinsuke Nakajima, Yoichi Inagaki, and Reyn Nakamoto, “Prophetic Blogger Identification Based on Buzzword Prediction Ability”, International Journal of Web Information Systems, Vol. 12, No. 3, pp.267-291, August 2016.
  2. Keisuke Hamada, Shinsuke Nakajima, Daisuke Kitayama, Kazutoshi Sumiya, Route Recommendation Method Based on Driver's Estimated Intention Considering Route Selection with Car Navigation, IAENG Transaction on Engineering Sciences:Special Issue for the International Association of Engineers Conferences 2014, World Scientific, pp.256-269, May 2015.
  3. Seiya Tomonaga, Shinsuke Nakajima, Yoichi Inagaki, Reyn Nakamoto, Jianwei Zhang : “Analyzing Early Mentioning of Past Buzzwords for Determination of Bloggers’ Buzzword Prediction Ability”, Transactions on Engineering Technologies, International MultiConference of Engineers and Computer Scientists 2014, pp.353-367, Springer Netherlands, Jan. 2015.
  4. Mayumi Ueda, Shinsuke Nakajima : “Cooking Recipe Recommendation Method Focusing on the Relationship Between User Preference and Ingredient Quantity”, Transactions on Engineering Technologies, International MultiConference of Engineers and Computer Scientists 2014, pp.385-395, Springer Netherlands, Jan. 2015.
  5. Daisuke Kitayama, Keisuke Ozu, Shinsuke Nakajima, Kazutoshi Sumiya, “A Route Recommender System Based on the User's Visit Duration at Sightseeing Locations”, Software Engineering Research, Management and Applications, Studies in Computational Intelligence Volume 578, 2015, pp 177-190, Springer International Publishing, Nov. 2014. (ACIT2014 Best Paper)
  6. Tomofumi Yoshida, Daisuke Kitayama, Shinsuke Nakajima and Kazutoshi Sumiya, A Tourist Spot Search Method Using Similarity of Function Based on Distributed Representations of User Reviews, International MultiConference of Engineers and Computer Scientists 2017, ICICWS2017 pp473-478, March 2017.
  7. Junya Yamazaki, and Shinsuke Nakajima, Serendipity-Oriented Recommender System Considering Product Awareness in Communities, International MultiConference of Engineers and Computer Scientists 2017, ICICWS2017 pp461-465, March 2017.
  8. Yuki Matsunami, Asami Okuda, Mayumi Ueda, and Shinsuke Nakajima, User Similarity Calculating Method for Cosmetic Review Recommender System, International MultiConference of Engineers and Computer Scientists 2017, ICDMA2017 pp312-316, March 2017.
  9. Keisuke Hamada, Shinsuke Nakajima, Daisuke Kitayama, and Kazutoshi Sumiya, “Experimental Evaluation of Method for Driving Route Recommendation and Learning Drivers' Route Selection Preferences”, The 18th International Conference on Information Integration and Web-based Applications & Services(iiWAS2016), pp.18-27, 2016.11.
  10. Yuriko Yamaguchi, Mimpei Morishita, Yoichi Inagaki, Reyn Nakamoto, Jianwei Zhang, Junichi Aoi, and Shinsuke Nakajima, “Web Advertising Recommender System Based on Estimating Users' Latent Interests”, The 18th International Conference on Information Integration and Web-based Applications & Services(iiWAS2016), pp.44-51, 2016.11.
  11. Mayummi Ueda, Yukitoshi Morishita, Tomiyo Nakamura, Natsuhiko Takata, and Shinsuke Nakajima, “Recipe Recommender System by Considering User’s Moods”, The 18th International Conference on Information Integration and Web-based Applications & Services(iiWAS2016), pp.474-478, 2016.11.
  12. John O'Donovan, Shinsuke Nakajima, Tobias Höllerer, Mayumi Ueda, Yuuki Matsunami, Byungkyu Kang, A Cross-Cultural Analysis of Explanations for Product Reviews, Proceedings of the Joint Workshop on Interfaces and Human Decision Making for Recommender Systems (IntRS 2016) co-located with ACM Conference on Recommender Systems (RecSys 2016), pp55-58, September 2016.
  13. Yuuki Matsunami, Mayumi Ueda, Shinsuke Nakajima, Takeru Hashikami, Sunao Iwasaki, John O'Donovan, and Byungkyu Kang, Explaining Item Ratings in Cosmetic Product Reviews, International MultiConference of Engineers and Computer Scientists 2016, ICICWS2016 pp392-397, March 2016.
  14. Natsuhiko Takata, Mayumi Ueda, Yukitoshi Morishita, and Shinsuke Nakajima, Automatic Recipe Metadata Generating Method by Considering Users' Various Moods, International MultiConference of Engineers and Computer Scientists 2016, ICICWS2016 pp413-418, March 2016.
  15. Jianwei Zhang, Seiya Tomonaga, Shinsuke Nakajima, Yoichi Inagaki, and Reyn Nakamoto, “Finding Prophets in the Blogosphere: Bloggers Who Predicted Buzzwords Before They Become Popular”, Proc. The 17th International Conference on Information Integration and Web-based Applications & Services (iiWAS 2015), pp. 100-109, Brussels, Belgium, December 2015.