Mendeley's Data and Perspectives on Data Challenges

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Presentation given at the RecSysChallenge workshop (http://2012.recsyschallenge.com/) at Recommender Systems 2012 (http://recsys.acm.org/2012/).

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Mendeley's Data and Perspectives on Data Challenges

  1. 1. Mendeleys Data andPerspectives on Data Challenges Kris Jack, PhD Chief Data Scientist https://twitter.com/_krisjack
  2. 2. Overview➔ Whats Mendeley?➔ Why Run Challenges?➔ Mendeleys Challenges➔ Conclusions
  3. 3. Whats Mendeley?
  4. 4. ➔ Mendeley is a platform that connects researchers, research data and apps Mendeley Open API➔ How are we building our community?
  5. 5. Mendeley provides tools to help users......organisetheir research ➔ Reference management ➔ Cite-as-you- write ➔ Full-text article search ➔ Digitalised annotations
  6. 6. Mendeley provides tools to help users... ...collaborate with one another...organisetheir research ➔ Professional research groups ➔ Social network ➔ Annotation sharing
  7. 7. Mendeley provides tools to help users... ...collaborate with one another...organise ...discover newtheir research research ➔ Personalised article recommendations ➔ Related research ➔ Research contact suggestions
  8. 8. Our community from a data perspectiveSocial network Personal libraries (~2M users) (~300M articles) Research groups Research catalogue (~175K groups) (~50M unique articles)
  9. 9. Why RunChallenges?
  10. 10. Why Run Challenges?➔ An important part of our mission is to make science more open
  11. 11. Why Run Challenges?➔ An important part of our mission is to make science more open “All the time we are very conscious of the huge challenges that human society has now – curing cancer, understanding the brain for Alzheimer‘s [...].
  12. 12. Why Run Challenges?➔ An important part of our mission is to make science more open “All the time we are very conscious of the huge challenges that human society has now – curing cancer, understanding the brain for Alzheimer‘s [...]. But a lot of the state of knowledge of the human race is sitting in the scientists’ computers, and is currently not shared […] We need to get it unlocked so we can tackle those huge problems.“
  13. 13. Why Run Challenges?➔ An important part of our mission is to make science more open “All the time we are very conscious of the huge challenges that human society has now – curing cancer, understanding the brain for Alzheimer‘s [...]. But a lot of the state of knowledge of the human race is sitting in the➔ We run challenges that scientists’ computers, and is aim to open up science currently not shared […] We need to get it unlocked so we can tackle➔ Your skills in information those huge problems.“ sciences are valuable to us
  14. 14. MendeleysChallenges
  15. 15. PloS/Mendeleys Binary BattleChallenge: Build an application with our data, make science more open.Results: More details at http://dev.mendeley.com/api-binary-battle/
  16. 16. ScienceRec Challenge 2012Challenge: Build off-line system for scientific recommendations with our API and DataTEL data setResults: Will discuss today How to improve for the future?50K users, with at least 20 articles each More details at http://2012.recsyschallenge.com/tracks/sciencerec/
  17. 17. Conclusions
  18. 18. Conclusions➔ Mendeley makes tools that help researchers to: ➔ organise their research ➔ collaborate with one another ➔ discover new research➔ We are crowdsourcing a wealth of research data➔ Were opening it up to the world➔ And inviting you to participate
  19. 19. Were Hiring!➔ Data Scientist ➔ apply recommender technologies to Mendeleys data ➔ work on improving the quality of Mendeleys research catalogue ➔ starting in first quarter of 2013 ➔ 6 month secondment in KNOW Center, TU Graz, Austria as part of the EC FP7 TEAM project (http://team-project.tugraz.at/)➔ http://www.mendeley.com/careers/
  20. 20. www.mendeley.com
  21. 21. A Challenge for the Future?Challenge: Investigate how well algorithms perform in real-world settingsMotivation: Industry repeatedly finds that aggressive A/B testing is required because offline improvements do not necessarily translate to online improvementsProblem: Academia tends not to have access to large online communities Research groups (~175K groups)Solution: Industry runs A/B test with academic algorithms and reports resultsWhat about privacy? Use publicly available data Anonymise and aggregate results reported

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