Synthese Recommender
From CISTI-ICIST LAB WIKI
Principal Investigator: Web page: Andre Vellino, Email: andre.vellino@nrc.ca
The Synthese Project aims to assess the effectiveness of recommender systems for Scientific Technical and Medical (STM) digital library portal. We want to enhance the process of scientific innovation by providing serendipitous, personalized article recommendations based on a hybrid, content-based and item-based collaborative filtering capability.
Contents |
Try the Synthese Demo
- Try the Synthese Recommender System Demo and view the Flash Tour of Synthese.
- Note that the current demo only uses collaborative filtering between users and article citations. Full-text search and content-based filtering will be included in the next version.
Papers and Presentations on Synthese
- Vellino, A. and Zeber, D (2007) A Hybrid, Multi-Dimensional Recommender for Journal Articles in a Scientific Digital Library Proceedings of the Workshop on Web Personalization and Recommender Systems At the ACM International Conference on Web Intelligence, Silicon Valley, CA, November 2007.
- Slideshare presentation on Synthese given at the above workshop. There is also a French / English bilingual version of a similar presentation.
- Vellino, A. (2009) Recommending Journal Articles with PageRank Ratings Submitted to 3rd ACM Conference on Recommender Systems, 2009.
- M. F. Rutledge-Taylor, A. Vellino and R. L. West. (2008) A Holographic Associative Memory Recommender System, 3rd International Conference on Digital Information Management (ICDM 2008), London
Related Software
- TechLens Demo of a Digital Library recommender from the University of Minnesota, whose design inspired Synthese
- Taste Java collaborative filtering software used to build Synthese.
References
- Collaborative Filtering bibliography by James Thornton.
- Desmond Elliott James Rutherford and John Erickson A Recommender System for the DSpace Open Repository Platform HP Labs technical report, 2008
- S. Berkovsky, T. Kuflik, and F. Ricci. Distributed collaborative filtering with domain specialization. In ACM Recommender Systems 2007, October 19-20, 2007, Minneapolis, Minnesota, USA, 2007.
- Adomavicius, G. and Tuzhilin, A. (2005) Toward the Next Generation of Recommender Systems: A Survey of the State-of-the-Art and Possible Extensions IEEE Transactions on Knowledge and Data Engineering, 17(6):734-749.
- Smeaton, A. F. and Callan, J. (2005). Personalisation and recommender systems in digital libraries. International Journal on Digital Libraries, V5(4):299-308.
- Torres, R., Mcnee, S. M., Abel, M., Konstan, J. A., and Riedl, J. (2004). Enhancing digital libraries with techlens+. Proceedings of the 4th ACM/IEEE-CS Joint Conference on Digital Libraries, pages 228-236, New York, NY, USA. ACM Press.
- Webster, J., Jung, S., and Herlocker, J. (2004). Collaborative filtering: A new approach to searching digital libraries. New Review of Information Networking, 10(2):177-191.
