A Multi-criteria collaborative filtering approach for research paper recommendation in papyres

Lecture Notes in Business Information Processing

Volumn 26 LNBIP, Issue , 2009, Pages 25-39

  Naak, Amine ^a   Hage, Hicham ^a   Aïmeur, Esma ^a  

^a UNIVERSITÉ DE MONTRÉAL   (Canada)

Author keywords

Collaborative filtering; EEducation; Multi criteria recommendation; Research paper recommendation

Indexed keywords

BIBLIOGRAPHIES; INFORMATION SERVICES; KNOWLEDGE ACQUISITION; PAPER; SIGNAL FILTERING AND PREDICTION;

COLLABORATIVE FILTERING; CONTENT-BASED; DOCUMENT MANAGEMENT TOOLS; EEDUCATION; GRADUATE STUDENTS; HYBRID RECOMMENDER SYSTEMS; MANAGEMENT SYSTEMS; MULTI-CRITERIA; MULTI-CRITERIA APPROACH; MULTI-CRITERIA RECOMMENDATION; NEIGHBOURHOOD; RECOMMENDATION TECHNIQUES; RESEARCH PAPER RECOMMENDATION; RESEARCH PAPERS; SHARE KNOWLEDGE;

RESEARCH;

EDUCATION; FILTRATION; INFORMATION SYSTEMS; RESEARCH;

EID: 67249132813     PISSN: 18651348     EISSN: None     Source Type: Book Series    
DOI: 10.1007/978-3-642-01187-0_3     Document Type: Conference Paper

References (19)

1. Brusilovsky, P., Farzan, R., Jae-wook, A.: Comprehensive personalized information access in an educational digital library. In: 5th ACM/IEEE-CS Joint Conference on Digital Li- braries, Denver, CO, USA, pp. 9-18 (2005)
2. Kapoor, N., Chen, J., Butler, J.T., Fouty, G.C., Stemper, J.A., Riedl, J., Konstan, J.A.: Techlens: a researcher's desktop. In: ACM Conference on Recommender Systems (RecSys 2007), Minneapolis, MN, USA, pp. 183-184 (2007)
3. Torres, R., McNee, S., Abel, M., Konstan, J., Riedl, J.: Enhancing digital libraries with TechLens+. In: 4th ACM/IEEE-CS joint conference on Digital libraries (JCDL 2004), Tuscon, USA, pp. 228-236 (2004)
4. Huang, X., An, A., Cercone, N., Promhouse, G.: Discovery of Interesting Association Rules from Livelink Web Log Data. In: IEEE International Conference on Data Mining (ICDM 2002), Maebashi, Japan, pp. 763-766 (2002)
5. Naak, A., Hage, H., Aïmeur, E.: Papyres: a Research Paper Management System. In: IEEE Joint Conference on E-Commerce Technology (CEC 2008) and Enterprise Computing, E- Commerce and E-Services (EEE 2008), Crystal City, Washington (2008)
6. O'Reilly, T.: What Is Web 2.0 (2005) (accessed, January 2008), http://www.oreillynet.com/
7. Adomavicius, G., Tuzhilin, A.: 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 (2005)
8. Lakiotaki, K., Tsafarakis, S., Matsatsinis, N.: UTA-Rec: a recommender system based on multiple criteria analysis. In: ACM Conference on Recommender Systems (RecSys 2008), Lausanne, Switzerland, pp. 219-226 (2008)
9. Matsatsinis, N.F., Kleanthi, L., Pavlos, D.: A System based on Multiple Criteria Analysis for Scientific Paper Recommendation. In: 11th Panhellenic Conference in Informatics, Patras, Greece, pp. 135-149 (2007)
10. Vassileva, J.: Harnessing P2P Power in the Classroom. In: Lester, J.C., Vicari, R.M., Para- guaçu, F. (eds.) ITS 2004. LNCS, vol. 3220, pp. 305-314. Springer, Heidelberg (2004)
11. Tang, T.Y.: The design and study of pedagogical paper recommendation. Doctoral Thesis. University of Saskatchewan, Saskatoon (2008)
12. Tang, T.Y., McCalla, G.I.: A multi-dimensional paper recommender. In: 13th International Conference on Artificial Intelligence in Education Marina Del Rey, Los Angeles, Califor- nia, U.S.A (2007)
13. Mao, Y., Vassileva, J., Grassmann, W.: A System Dynamics Approach to Study Virtual Communities. In: 40th Annual Hawaii International Conference on System Sciences, Wai- koloa, Hawaii, p. 178a (2007)
14. Bollacker, K., Lawrence, S., Giles, L.: A System for Automatic Personalized Tracking of Scientific Literature on the Web. In: 4th ACM Conference on Digital Libraries, Berkeley, California, United States, pp. 105-113 (1999)
15. Burke, R.: Hybrid Recommender Systems: Survey and Experiments. User Modeling and User-Adapted Interaction 12(4), 331-370 (2002)
16. IEEE Standard for Learning Object Metadata. IEEE Std 1484.12.1-2002, i-32 (2002)
17. Melville, P., Mooney, R.J., Nagarajan, R.: Content-boosted collaborative filtering for Im- proved recommendations. In: 18th National Conference on Artificial Intelligence, Edmonton, Alberta, Canada, pp. 187-192 (2002)
18. Adomavicius, G., Kwon, Y.: New Recommendation Techniques for Multicriteria Rating Systems. IEEE Intelligent Systems 22(3), 48-55 (2007)
19. Herlocker, J.L., Konstan, J.A., Terveen, L.G., Riedl, J.T.: Evaluating collaborative filtering recommender systems. ACM Trans. Inf. Syst. 22(1), 5-53 (2004)