The document discusses research on collaborative information sharing systems and participative systems. Specifically, it discusses using semantics to help organize information contributed by users on collaborative systems like wikis and folksonomies. It proposes using ontologies and semantic annotations on different levels of wiki systems and expanding folksonomies with ontologies to address limitations like lack of hierarchy, precision and recall in folksonomies. Fuzzy set theory is also discussed as a way to describe resources through membership in categories defined by tags to enable more intuitive querying of folksonomies.

1. Research on collaborative information sharing systems Davide Eynard [email_address] Dipartimento di Elettronica e Informazione Politecnico di Milano

2. Intro What I'm doing Collaborative systems Semantic Web Semantic Wikis Folksonomies

3. What I'm doing “Research on collaborative information sharing systems” They are designed to help people involved in a common task achieve their goals Actually, they do not only allow for information sharing, but also for collaborative work There are plenty of them: we are focusing on some we call participative

4. Collaborative encyclopedias

5. Collaborative playlists

6. Collaborative music

7. Collaborative docs

8. Collaborative maps

9. Collaborative slide collections

10. Collaborative word processing

11. Collaborative bookmarking

12. Collaborative news

13. Why? Why are collaborative systems having so much success lately? Give a look at “ What is Web2.0 ” design patterns: The long tail Data is the next Intel Inside Users add value Network effects by default Some rights reserved The perpetual beta Cooperate, don't control Software above the level of the single device

14. How? How can you make your users actively contribute to a project? Instant gratification i.e. Napster, CDDB (now FreeDB, MusicBrainz) Communities of practice ( Etienne Wenger ) User interface So, systems should be very easy to use provide an immediate reward do most of the hard work automatically

15. What? What do participative systems and Semantic Web have in common?

16. What? What do participative systems and Semantic Web have in common? “ The Semantic Web is not a separate Web but an extension of the current one, in which information is given well-defined meaning, better enabling computers and people to work in cooperation” Tim Berners-Lee, 2001

17. What is Semantic Web? HAH! 10^9$ Question! Semantic Web is not “making machines understand stuff” Semantic Web is about standards reasoning interoperability metadata (client-server-server model) ie. annotations, classifications, ratings, etc.

18. Glasses

19. PowerGlasses

20. And now... A little presentation by this (great) man: Michael Wesch Assistant professor of Cultural Anthropology Kansas State University

21. So again... what? What do participative systems and Semantic Web have in common? Participative systems work thanks to contributions by people unstructured information, by humans for humans hard to find and organize Semantic Web works thanks to structured information not easy to publish, need more participation So, why don't we use semantics to help people organize and find stuff people to help Semantic Web bootstrap

22. Our work Our work is focused on two main fields: Semantic Wikis Wiki as in “Wikipedia”... ... but also (well, mostly) in enterprises Folksonomies expanding them with ontologies relations between users, resources, tags description of different families of tags applications

23. Semantic Wikis Wikis are one of the best examples of “read/write” Web they allow any user to easily create, modify, delete any page but the information is just plain, unstructured text: no interoperability, no way to organize them

24. Current approaches on SWikis semantics added inside pages pages as concepts and relations within them semantics added as metadata tags which describe the pages our approach: semantics on different levels wiki system context contents upper ontology

25. Folksonomies Term by Thomas Vander Wal (2004) “folks” + “taxonomy” First (and most cited) websites: flickr del.icio.us Growing interest users increase exponentially (1.5M in deli)

26. Advantages of folksonomies Folksonomies: are inclusive are current offer discovery are non-binary are democratic and self-moderating follow “desire lines” offer insight into user behavior are usable with a low cost

27. Limits of folksonomies Limits of folksonomies: no synonym control “basic level” variations lack of precision lack of recall (!) lack of hierarchy gaming no real standard

28. Limits of folksonomies

29. Limits of folksonomies

30. Limits of folksonomies

31. Studying folksonomies Tag usage and tag families Expanding folksonomies with ontologies Fuzzy queries inside folksonomies

32. Tag usage Power law distribution

33. Tag usage “Words with meaning” - 114 recognized words out of the 140 most used tags (81.43%) - follow power law distribution

34. Tag families Identifying what (or who) it is about Identifying what it is Identifying who owns it Refining categories Identifying qualities or characteristics Self reference Task organizing

35. Fuzzy queries

36. Fuzzy queries

37. Fuzzy queries The basic idea is that we could model resources belonging to one or more categories through fuzzy sets instead of crisp ones To assign the membership value of a particular resource r with respect to a particular tag t , we calculate the ratio #users who tagged r as “ t” #users who saved r using any tag

38. Fuzzy queries Then we describe our fuzzy set with five fuzzy labels

39. Fuzzy queries: results A way to describe resources through tags

40. Fuzzy queries: results A way to describe resources through tags A way to query folksonomies with a more intuitive interface to filter information ie. search for “very programming and not much java”

41. Fuzzy queries: results A way to describe resources through tags A way to query folksonomies with a more intuitive interface to filter information ie. search for “very programming and not much java” A way to learn something more about tag families ie. tag “toread”

42. Fuzzy queries: results A way to describe resources through tags A way to query folksonomies with a more intuitive interface to filter information ie. search for “very programming and not much java” A way to learn something more about tag families ie. tag “toread” A major drawback: the system is quite slow

43. That's All, Folks Thank you! Questions are welcome