Abstract
We describe the use of the social reference management website CiteULike for recommending scientific articles to users, based on their reference library. We test three different collaborative filtering algorithms, and find that user-based filtering performs best. A temporal analysis of the data indexed by CiteULike shows that it takes about two years for the cold-start problem to disappear and recommendation performance to improve.
Original language | English |
---|---|
Title of host publication | RecSys'08 : Proceedings of the 2008 ACM Conference on Recommender Systems |
Number of pages | 4 |
Publication date | 1 Dec 2008 |
Pages | 287-290 |
ISBN (Print) | 9781605580937 |
DOIs | |
Publication status | Published - 1 Dec 2008 |
Externally published | Yes |
Event | 2008 2nd ACM International Conference on Recommender Systems, RecSys'08 - Lausanne, Switzerland Duration: 23 Oct 2008 → 25 Oct 2008 |
Conference
Conference | 2008 2nd ACM International Conference on Recommender Systems, RecSys'08 |
---|---|
Country/Territory | Switzerland |
City | Lausanne |
Period | 23/10/2008 → 25/10/2008 |
Keywords
- Reference management
- Collaborative filtering
- Recommendation systems
- Cold-start problem
- Temporal analysis