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A FEDERATED SEARCH AND
        SOCIAL RECOMMENDATION
                 WIDGET
          Sten Govaerts, Sandy El Helou, Erik Duval and Denis Gillet.




Saturday 19 March 2011
WHAT’S A WIDGET ?!?




Saturday 19 March 2011
WHAT’S A WIDGET ?!?




Saturday 19 March 2011
WHAT’S A WIDGET ?!?




Saturday 19 March 2011
WHAT’S A WIDGET ?!?




Saturday 19 March 2011
WHAT’S A WIDGET ?!?




Saturday 19 March 2011
CONTEXT
    • Personal            Learning Environment:
         • customizable
         • re-use, creation        & mashup of tools, resources
    • enable             users to access content
         • in     different contexts




Saturday 19 March 2011
CONTEXT
    • Personal            Learning Environment:
         • customizable
         • re-use, creation        & mashup of tools, resources
    • enable             users to access content
         • in     different contexts




Saturday 19 March 2011
CONTEXT
    • Personal            Learning Environment:
         • customizable
         • re-use, creation        & mashup of tools, resources
    • enable             users to access content
         • in     different contexts




Saturday 19 March 2011
ARCHITECTURE




Saturday 19 March 2011
ARCHITECTURE




Saturday 19 March 2011
ARCHITECTURE




Saturday 19 March 2011
ARCHITECTURE




Saturday 19 March 2011
ARCHITECTURE




Saturday 19 March 2011
ARCHITECTURE




Saturday 19 March 2011
ARCHITECTURE




Saturday 19 March 2011
ARCHITECTURE




Saturday 19 March 2011
ARCHITECTURE




Saturday 19 March 2011
ARCHITECTURE




Saturday 19 March 2011
DEMO...




Saturday 19 March 2011
DEMO...




Saturday 19 March 2011
DEMO...




Saturday 19 March 2011
DEMO...




Saturday 19 March 2011
PAGE RANK
                         HYPERLINK
               WEB
               SITE
                                          Rank of node i:




                                     A node is important if and only if many other
                                             important nodes point to it




Saturday 19 March 2011
OUR CASE
                                                                                  hare
                                                                                       d    R1
                                                                           d   /s
                                                                    save
                                                                      saved/shared
                                                  d
                                                en tion
                                                           Sten                             R2
                                            fr i e c                      dis
                                                n                            like
                                           c on                                  d
                                                                  lik
                                                                     ed
                                                                                           R3
                               d n
                                       Sandy
                            ien ctio
                          fr e
                         c on
                             n                     lik
                                                      ed
                                                                                  R4

                 Erik                                       R5




Saturday 19 March 2011
NOW FOR MULTI-DIRECTIONAL,
        PERSONALIZED & CONTEXTUAL RANKING




                         A node is important to a particular set of nodes (representing the
                         target user and the context) if and only if many important nodes
                         connected to this root set, via important relation types, point to it

Saturday 19 March 2011
EVALUATION

    • 15        PhD students at K.U. Leuven and EPFL.

    •   What?

         • usability

         • user          satisfaction

         • usefulness



Saturday 19 March 2011
FIRST PHASE
    • current            media search tool: Google & YouTube




    • understanding            recommendations: 6/15 from like/dislike

Saturday 19 March 2011
FIRST PHASE
    • current            media search tool: Google & YouTube




    • understanding            recommendations: 6/15 from like/dislike

Saturday 19 March 2011
FIRST PHASE
    • current            media search tool: Google & YouTube




    • understanding            recommendations: 6/15 from like/dislike

Saturday 19 March 2011
FIRST PHASE
    • current            media search tool: Google & YouTube




    • understanding            recommendations: 6/15 from like/dislike

Saturday 19 March 2011
FIRST PHASE
    • current            media search tool: Google & YouTube




    • understanding            recommendations: 6/15 from like/dislike

Saturday 19 March 2011
FIRST PHASE
    • current            media search tool: Google & YouTube




    • understanding            recommendations: 6/15 from like/dislike

Saturday 19 March 2011
FIRST PHASE
    • current            media search tool: Google & YouTube




    • understanding            recommendations: 6/15 from like/dislike

Saturday 19 March 2011
SECOND PHASE




Saturday 19 March 2011
SECOND PHASE
    • only         14 participants (one less)
    •   open questions
    • usefulness          of recommendations: 11/14 pro.
    • user   satisfaction: System Usability Scale (SUS) & MS
        Desirability Toolkit
    • SUS          score: 66,25%
         •2      groups

Saturday 19 March 2011
SECOND PHASE
    • only         14 participants (one less)
    •   open questions
    • usefulness          of recommendations: 11/14 pro.
    • user   satisfaction: System Usability Scale (SUS) & MS
        Desirability Toolkit
    • SUS          score: 66,25%
         •2                                     K.U. Leuven: high (75%)
                 groups
                                           EPFL + one K.U.Leuven: low (50%)

Saturday 19 March 2011
WHY THE DIFFERENT SUS?



    • 1st        phase by 2 interviewers




Saturday 19 March 2011
WHY THE DIFFERENT SUS?



    • 1st        phase by 2 interviewers




Saturday 19 March 2011
WHY THE DIFFERENT SUS?



    • 1st        phase by 2 interviewers




Saturday 19 March 2011
WHY THE DIFFERENT SUS?

    •   issues:

         • distracts       of unrelated widget’s UI updates.

         • layout        too dense

         • height        of widgets too small

    • KULeuven             student had prior experience with iGoogle.

    • not         evaluating the widget but the whole experience...

Saturday 19 March 2011
DESIRABILITY...




Saturday 19 March 2011
DESIRABILITY...




Saturday 19 March 2011
DESIRABILITY...




Saturday 19 March 2011
DESIRABILITY...




Saturday 19 March 2011
DESIRABILITY...




Saturday 19 March 2011
DESIRABILITY...




Saturday 19 March 2011
DESIRABILITY...




Saturday 19 March 2011
DESIRABILITY...




Saturday 19 March 2011
DESIRABILITY...




Saturday 19 March 2011
DESIRABILITY...




Saturday 19 March 2011
DESIRABILITY...




Saturday 19 March 2011
DESIRABILITY...




Saturday 19 March 2011
DESIRABILITY...




Saturday 19 March 2011
RECOMMENDATIONS
                            EVALUATION
    • compare    recommendations to their favourite
        tool: Google
         •2       groups with different queries




Saturday 19 March 2011
RECOMMENDATIONS
                            EVALUATION
    • compare    recommendations to their favourite
        tool: Google
         •2       groups with different queries
                         # relevant items returned
    Precision =
                          # total items returned




Saturday 19 March 2011
RECOMMENDATIONS
                            EVALUATION
    • compare    recommendations to their favourite
        tool: Google
         •2       groups with different queries

    Precision # relevant items returned in top N list
             =
      at N     # total items returned




Saturday 19 March 2011
RECOMMENDATIONS
                            EVALUATION
    • compare    recommendations to their favourite
        tool: Google
         •2       groups with different queries

    Precision # relevant items returned in top N list
             =
      at N     # total items returned

    • Google:            more relevant results
         • Google:        avg. prec. at 10 = 65%
         • widget:        avg. prec. at 10 = 50%
Saturday 19 March 2011
RECOMMENDATIONS
                            EVALUATION
    • compare    recommendations to their favourite
        tool: Google
         •2       groups with different queries

    Precision # relevant items returned in top N list
             =
      at N     # total items returned

    • Google:            more relevant results
         • Google:        avg. prec. at 10 = 65% less variation
         • widget:        avg. prec. at 10 = 50%   in results
Saturday 19 March 2011
FIXES...




Saturday 19 March 2011
FIXES...




Saturday 19 March 2011
FIXES...




Saturday 19 March 2011
FIXES...




Saturday 19 March 2011
FUTURE WORK

    • evaluation    in larger scale real-world
        situation (university + business)

    • evaluate  user satisfaction of widget
        and not container

    • evaluate   the recommendations
        further (based on use).

    • make               recommendations transparent

Saturday 19 March 2011
MORE VISUAL SEARCH...




Saturday 19 March 2011
THANK YOU!
                         QUESTIONS?...
Saturday 19 March 2011

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A Federated Search and Social Recommendation Widget