Exploiting the wisdom of social connections to make personalized recommendations on scholarly articles

Journal of Intelligent Information Systems

Volumn 42, Issue 3, 2014, Pages 371-391

  Pera, Maria Soledad ^a   Ng, Yiu Kai ^a  

^a 3361 TMCB   (United States)

Author keywords

CiteULike; Recommendation system; Scholarly article; Word similarity

Indexed keywords

ARTIFICIAL INTELLIGENCE; INFORMATION SYSTEMS; RECOMMENDER SYSTEMS;

ACADEMIC PUBLICATIONS; CITEULIKE; PERSONALIZED RECOMMENDATION; RESEARCH INTERESTS; SCHOLARLY ARTICLES; SCHOLARLY PUBLICATION; SOCIAL BOOKMARKING; WORD SIMILARITY;

PUBLISHING;

EID: 84901635785     PISSN: 09259902     EISSN: 15737675     Source Type: Journal    
DOI: 10.1007/s10844-013-0298-8     Document Type: Article

References (29)

1. Adomavicius, G., & Kwon, Y. (2012). Improving aggregate recommendation diversity using ranking-based techniques. IEEE Transactions on Knowledge and Data Engineering (TKDE), 24, 896-911.
2. Basu, C., Hirsh, H., Cohen, W., Nevill-Manning, C. (2001). Technical paper recommendation: a study in combining multiple information sources. Journal of Artificial Intelligence Research (JAIR), 1, 231-252.
3. Belem, F., Martings, E., Pontes, T., Almeida, J., Goncalves, M. (2011). Associative tag recommendation exploiting multiple textual features. In International ACM conference on research and development in information retrieval (SIGIR) (pp. 1033-1042).
4. Bellogin, A., Cantador, I., Castells, P. (2010). A study of heterogeneity in recommendations for a social music service. In International workshop on information heterogeneity and fusion in recommender systems (pp. 1-8).
5. Bogers, T., & van den Bosch, A. (2008). Recommending scientific articles using CiteULike. In ACM conference on recommender systems (RecSys) (pp. 287-290).
6. Bogers, T., & van den Bosch, A. (2011). Fusing recommendations for social bookmarking websites. International Journal of Electronic Commerce (IJEC), 15(3), 33-75.
7. Bourke, S., McCarthy, K., Smyth, B. (2011). Power to the people, exploring neighbourhood formations in social recommender system. In ACM conference on recommender systems (RecSys) (pp. 337-340).
8. Croft, W., Metzler, D., Strohman, T. (2010). Search engines: information retrieval in practice. Addison Wesley.
9. De Francisci Morales, G., Gionis, A., Lucchese, C. (2012). From chatter to headlines, harnessing the realtime web for personalized news recommendation. In ACM international conference on web search and data mining (WSDM) (pp. 153-162).
10. Ekstrand, M., Kannan, P., Stemper, J., Butler, J., Konstan, J., Riedl, J. (2010). Automatically building research reading lists. In ACM conference on recommender systems (RecSys) (pp. 159-166).
11. Guan, Z.,Wang, C., Bu, J., Chen, C., Yang, K., Cai, D., He, X. (2010). Document recommendation in social tagging services. In International world wide web conferences (WWW) (pp. 391-400).
12. Hoscher, C., & Strube, G. (2000). Web search behavior of internet experts and newbies. Computer Networks, 33, 337-346.
13. Jiang, Y., Jia, A., Feng, Y., Zhao, D. (2012). Recommending academic papers via users' reading purposes. In ACM conference on recommender systems (RecSys) (pp. 241-244).
14. Joachims, T. (2002). Optimizing search engines using click-through data. In ACM SIGKDD conference on knowledge, discovery, and data mining (pp. 133-142).
15. Knijnenburg, B., Bostandjiev, S., O'Donovan, J., Kobsa, A. (2012). Inspectability and control in social recommenders. In ACM conference on recommender systems (RecSys) (pp. 43-50).
16. Koberstein, J., & Ng, Y.-K. (2006). Using word clusters to detect similar web documents. In Second international conference on knowledge science, engineering, and management (KSEM 2007) (pp. 215-228).
17. Konstas, I., Stathopoulos, V., Jose, J. (2009). On social networks and collaborative recommendation. In International ACM conference on research and development in information retrieval (SIGIR) (pp. 195-202).
18. Koren, Y. (2010). Factor in the neighbors: scalable and accurate collaborative filtering. ACM Transactions on Knowledge Discovery from Data (TKDD), 4(1): 24. Article 1.
19. Ma, H., Zhou, D., Liu, C., Lyu, M., King, I. (2011). Recommender systems with social regularization. In ACM international conference on web search and data mining (WSDM) (pp. 287-296).
20. McNee, S., Kapoor, N., Konstan, J. (2006). Don't look stupid: avoiding pitfalls when recommending research papers. In ACM conference on computer supported cooperative work (CSCW) (pp. 171-180).
21. Naak, A., Hage, H., Ameur, E. (2009). A multi-criteria collaborative filtering approach for research paper recommendation in papyres. In MCETECH (pp. 25-39).
22. Nascimento, C., Laender, A., da Silva, A., Goncalves, M. (2011). A source independent framework for research paper recommendation. In ACM/IEEE joint conference on digital libraries (JCDL) (297-306).
23. Neumann, A. (2009). A survey of recommender systems at major sti providers. In Recommender systems for information providers, contributions to management science (pp. 1-12). Physica-Verlag HD.
24. Parra, D., & Brusilovsky, P. (2009). Collaborative filtering for social tagging systems: an experiment with CiteULike. In ACM conference on recommender systems (RecSys) (pp. 237-240).
25. Pera, M.S., & Ng, Y.-K. (2011). A personalized recommendation system on scholarly publications. In ACM conference on information and knowledge management (CIKM) (pp. 2133-2136).
26. Pudhiyaveetil, A., Gauch, S., Luong, H., Eno, J. (2009). Conceptual recommender system for CiteSeerX. In ACM conference on recommender systems (RecSys) (pp. 241-244).
27. Ricci, F., Rokach, L., Shapira, B., Kantor, P. (2011). Recommender systems handbook. Springer.
28. Sugiyama, K., & Kan, M. (2010). Scholarly paper recommendation via user's recent research interests. In ACM/IEEE joint conference on digital libraries (JCDL) (pp. 29-38).
29. Zobel, J. (2004). Writing for computer science. Springer.