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Expert (and Novice) Finding Within Shared Workspaces 03/02/2008 DERI Conference Room

Expert (and Novice) Finding Within Shared Workspaces 03/02/2008 DERI Conference Room. Peyman Nasirifard peyman.nasirifard@deri.org. Agenda. How do I do it? Live Demo! Challenges Conclusion and Future Work Questions. How Do I Do It?. What do we use? We do NOT use email

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Expert (and Novice) Finding Within Shared Workspaces 03/02/2008 DERI Conference Room

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  1. Expert (and Novice) Finding Within Shared Workspaces03/02/2008DERI Conference Room Peyman Nasirifard peyman.nasirifard@deri.org

  2. Agenda • How do I do it? • Live Demo! • Challenges • Conclusion and Future Work • Questions

  3. How Do I Do It? • What do we use? • We do NOT use email • We do NOT use Wikipedia • We do NOT use Google (co-occurence, etc.) • We do NOT use DBLP • We DO use Online Shared Workspaces • Currently BSCW • We use two main elements / components of shared workspace • Log file: Contains the transactions within shared workspace • Document: Provides input for expertise extractor

  4. How Do I Do It? II • Analyzing documents to extract key phrases • Analyzing log files to see which persons did what events on what documents • Rule of Thumb: A user is expert in topic X, if s/he has created or revised a document that contains topic X. A user is familiar with topic Y, if s/he has just read a document that contains topic Y

  5. Live Demo! Demo-based computing: Demos are always better than boring presentations!

  6. Challenges • Ambiguity: “output parameter” is not really an expertise! • There is no 100% accurate and automated Key phrase extraction algorithm from a document • Solution: We had a semi-automated approach and we removed the terms with low confidences • Future work: We will enable end users to remove inappropriate terms from their profiles and the algorithm can “learn” or “be trained” • Organization Expertise profile vs. Person Expertise Profile • We noticed that in some organizations, a single person tackles always with shared workspace and this may generate some noises in expertise profiles • Solution: Building organization expertise profile besides person can address this issue • Purifying Log files • Some log records are noisy: They do not have the pre-assumed structure • Solution: We defined some patterns and excluded the records that do not follow the patterns • Expertise Granularity • Rule of Thumb is not fine-grained enough • Knud: Taking to account the version history of deliverables • Similar phrases: “Semantic Web” and “SIOC” are from the same domain. • This issue is still a hot challenge in research community • Solution: We are trying to address this issue using directory searches like DMOZ or Google directory search

  7. Future Work • Lots of enhancement can be considered • See previous slide • Developed as a hobby • Later it attracted Ecospace consortium • Tomorrow it will be demonstrated in the review meeting

  8. Have a nice day! Thank you!  Try tools yourself: http://epeyman.googlepages.com Questions?

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