Growing the Semantic Web with Inverse Semantic Search

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					Growing the Semantic Web with
   Inverse Semantic Search

       Hans-Jörg Happel, FZI Karlsruhe
 1st Workshop on Incentives for the Semantic Web (INSEMTIVE 2008)
       at ISWC 2008, Karlsruhe, Germany, October 26th, 2008




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                                                                               The Basis

 Metadata (and structured data) are useful for a lot of fancy things
   • Many kinds of search and retrieval tasks
   • „Task automation“ on the Semantic Web

 „Metadata“ can be „created“ in various ways
   • Exposure of existing structured data (e.g. DBPedia)
   • (Semi-)Automatic metadata creation
   • Human metadata creation (e.g. tagging, annotations)

 Access to metadata might be restricted
   • Different spheres of sharing (private, friends, world…) – even in
     Web 2.0 applications (e.g. Flickr, del.icio.us)


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                       Growing the Semantic Web with Inverse Semantic Search               2
                                                                      The Problem

 So metadata is a nice thing…but…
   • Metadata creation is costly
   • Metadata creation is decoupled from metadata use (concerning
     time and actors)

 No unified theory, why metadata is created and how it is shared
   • SemWeb Vision does not address the creator side of metadata –
     it spends a lot of effort to convince people using the Semantic
     Web but not contributing to it

 Research questions
   • How can individuals be guided to create the right metadata?
   • How can individuals be motivated to create this metadata?

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                      Growing the Semantic Web with Inverse Semantic Search         3
  Individual‘s incentives and disincentives
                           for contributions
 (Photo) tagging systems
   • Personal and social benefit (organizational, functional) [1, 2, 3]

 (Movie) rating systems
   • Uniqueness of contribution and goal setting [4]
   • Value and relationships [5]

 General knowledge management
   • Lack of personal benefit [6, 7, 8]
   • Privacy (expose information or expertise) [9, 10]
   • Effort (cost of knowledge capturing, categorization and setting
     access rights) [10, 11]


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                        Growing the Semantic Web with Inverse Semantic Search   4
                                                                                                  The Idea (1)
HOW IT WORKS NOW




                                                                                                  „Search“ leads to importing
                                                                                               metadata from the Semantic Web
                                                                                                to the private space of the user
                      Metadata creator                    Metadata user
                            actsIn(Casablanca,
                            +    Borgart)                   ?
                                            mentionedIn(Casablanca, ?x)
                                                                                                                       Evolution of the
                                                                                                                       Semantic Web
INVERSE SEM. SEARCH




                                                                                                                   „Inverse Search“ leads to
                                                                                                                   contributing metadata to
                                                                                                                   the public Semantic Web

                                                          Metadata user                         Metadata creator
                                                                                                            mentionedIn(Casablanca,
                                                            ?                                         ? !   +        Paris)


                                 mentionedIn(Casablanca, ?x)
                                                                                                                       Evolution of the
                                                                                                                       Semantic Web                5
                                              Growing the Semantic Web with Inverse Semantic Search                                            5
                                                                           The Idea (2)

 Inverse Semantic Search means
   • Share semantic queries instead of metadata (to preserve data
     privacy)
   • Derive an aggregated information need from the semantic queries
     of a community (to lower cost)
   • Display/use aggregated information need to acquire/share
     metadata in a focussed and selective way (to raise motivation)



 Initial concept lined out in the papers leaves further questions
   • Work with more complex semantic queries
   • Proper heuristics for deriving unsatisfied information needs
   • Applying reasoning to aggregate information needs
   • Embed principle in concrete application designs
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                       Growing the Semantic Web with Inverse Semantic Search              6
                                                                              Summary

 How can individuals be guided to create the right metadata?
   • Try to predict which metadata could be useful in the future
   • Inverse search as a meachnism to use semantic query logs for
     that purpose

 How can individuals be motivated to create this metadata?
   • Address feedback channels and easy sharing facilities in
     application design
   • Nice UIs with context-specific need representations („What is
     missing?“)




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                      Growing the Semantic Web with Inverse Semantic Search             7
                                                                                                    The End

 Thanks for your attention!

                                                                                                         www.team-project.eu


 Any questions?

                                                                                                           http://waves.fzi.de




 Further reading
   •   Happel, H.-J., Stojanovic, L.: Analyzing organizational information
       gaps. In: I-Know08: Proceedings of 8rd International Conference                                       Hans-Jörg Happel
       on Knowledge Management. (2008)
                                                                                              FZI Forschungszentrum Informatik
   •   Happel, H.-J.: Closing Information Gaps with Inverse Search. In
                                                                                                           Karlsruhe, Germany
       Proceedings of the 7th International Conference on Practical
       Aspects of Knowledge Management (PAKM2008) (to appear)
                                                                                                                 www.fzi.de/ipe
                                                                                                               {happel}@fzi.de


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                                      Growing the Semantic Web with Inverse Semantic Search                                       8
                                                                         Cited Literature
•   [1] Ames, M., Naaman, M.: Why we tag: motivations for annotation in mobile and online media. In: CHI ’07: Proceedings
    of the SIGCHI conference on Human factors in computing systems, New York, NY, USA, ACM (2007) 971–980
•   [2] Kustanowitz, J., Shneiderman, B.: Motivating annotation for personal digital photo libraries: Lowering barriers while
    raising incentives. Technical Report HCIL-2004-18, University of Maryland, College Park, MD, USA (01 2005)
•   [3] Marlow, C., Naaman, M., Boyd, D., Davis, M.: Ht06, tagging paper, taxonomy, flickr, academic article, to read. In:
    HYPERTEXT ’06: Proceedings of the seventeenth conference on Hypertext and hypermedia, New York, NY, USA, ACM
    2006) 31–40
•   [4] Beenen, G., Ling, K., Wang, X., Chang, K., Frankowski, D., Resnick, P., Kraut, R.E.: Using social psychology to
    motivate contributions to online communities. In: CSCW ’04: Proceedings of the 2004 ACM conference on Computer
    supported cooperative work, New York, NY, USA, ACM (2004) 212–221
•   [5] Rashid, A.M., Ling, K., Tassone, R.D., Resnick, P., Kraut, R., Riedl, J.: Motivating participation by displaying the value
    of contribution. In: CHI ’06: Proceedings of the SIGCHI conference on Human Factors in computing systems, New York,
    NY, USA, ACM (2006) 955–958
•   [6] Angel Cabrera and Elizabeth F. Cabrera. Knowledge-sharing dilemmas. Organization Studies, 23:687–710, 2002.
•   [7] Ulrike Cress and Friedrich-Wilhelm Hesse. Knowledge sharing in groups: experimental findings of how to overcome a
    social dilemma. In ICLS ’04: Proceedings of the 6th international conference on Learning sciences, pages 150–157.
    International Society of the Learning Sciences, 2004.
•   [8] Molly McLure Wasko and Samer Faraj. Why should i share? examining social capital and knowledge contribution in
    electronic networks of practice. MIS Quarterly, 29(1):35–57, 2005.
•   [9] Alexander Ardichvili, Vaughn Page, and Tim Wentling. Motivation and barriers to participation in virtual knowledge-
    sharing communities of practice. Journal of Knowledge Management, 7(1):64–77, 2003.
•   [10] Kevin C. Desouza. Barriers to effective use of knowledge management systems in software engineering. Commun.
    ACM, 46(1):99–101, 2003.
•   [11] Kevin C. Desouza and J. Roberto Evaristo. Managing knowledge in distributed projects. Commun. ACM, 47(4):87–
    91, 2004.



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                                         Metadata gaps




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                                 Types of queries




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Simple semantic query log




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                      High-level architecture & UI
              (for keyword-based Inverse Search)

Server




         Clients




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Inverse search (process perspective)




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