Recommendations in the Scientific World

1. Recommendations in the Scientific World John Delacruz Oct 8, 2007

2. Outline • Problems in science • Finding papers • Filtering and Merit • Journalfire • What is it? • Data set • Other data sets

3. Current Problem (Biology) • Finding papers • 739,303 articles in 2006 • ~20 journals per discipline • Filtering and merit • Journal title • 83% rejection rate

4. Solution • Recommendation system • Democratic rating system • New measures for merit • Stop relying on journal title

5. Journalfire

6. Recommendation systems • Content-based recommendations • The user will be recommended items similar to the ones the user preferred in the past • Collaborative recommendations • The user will be recommended items that people with similar tastes and preferences liked in the past • Hybrid approaches • These methods combine collaborative • and content-based methods Adomavicius and Tuzhilin, 2005

7. Pubmed Title Authors Journal Abstract MESH terms Date Journalfire Rating Tags Journal clubs User Favorites Date Journalfire data

8. Content based recommendations author author keywords article article journal date tags

9. Collaborative recommendations Adomavicius and Tuzhilin, 2005 article user lists article co-occurrence of articles

10. New collaborators keywords article article author author journal journal date

11. Other data sets

12. Faculty of 1000 6,500 ratings

13. Neurotree

14. Tagging