Search and Browsing Cycle
      for Knowledge
  Discovery and Learning
     Sebastian Ryszard Kruk
     sebastian.kruk@der...
Search and Browsing Cycle
      for Knowledge
  Discovery and Learning
     Sebastian Ryszard Kruk
     sebastian.kruk@der...
Take away message




                    2
                        2
Take away message


•   We search in different ways for different things




                                             ...
Take away message


•   We search in different ways for different things

•   Keyword search is not enough




           ...
Take away message


•   We search in different ways for different things

•   Keyword search is not enough

•   We create ...
Outline
•   Motivation

•   How do people search

•   Search and Browsing life-cycle

•   Applying semantics and making us...
Motivation




             4
Motivation

  How to discover and integrate knowledge
coming from both formal and informal sources?




                  ...
Motivation




How to share and interconnect knowledge among people?




                                                 ...
How do people search?
•   Different user goals:




                            5
                                5
How do people search?
•   Different user goals:

    – Resource Seeking - the user wants to find a specific
      resource (...
How do people search?
•   Different user goals:

    – Resource Seeking - the user wants to find a specific
      resource (...
How do people search?
•   Different user goals:

    – Resource Seeking - the user wants to find a specific
      resource (...
Search and browsing




                      6
                          6
Search and browsing
• Why?

   •   Knowledge can be useful

   •   Not everything is a useful knowledge




              ...
Search and browsing
• Why?

    •   Knowledge can be useful

    •   Not everything is a useful knowledge

• How? (Search ...
Search and browsing
• Why?

    •   Knowledge can be useful

    •   Not everything is a useful knowledge

• How? (Search ...
Search and browsing
• Why?

    •   Knowledge can be useful

    •   Not everything is a useful knowledge

• How? (Search ...
Search and browsing
• Why?

    •   Knowledge can be useful

    •   Not everything is a useful knowledge

• How? (Search ...
Keyword-based search
   Why is it not enough?




                           7
                               7
Keyword-based search
            Why is it not enough?


•   Too many results (low precision)

•   One needs to specify th...
Keyword-based search
   How we can improve?




                         8
                             8
Keyword-based search
            How we can improve?

•   Disambiguation through a context

    •   Long-term: user’s inte...
Keyword-based search
      What’s next?




                       9
                           9
Keyword-based search
                   What’s next?



•   “Tell me why” button and the transcript of refinement
    proce...
Faceted navigation
  Why we need that?




                      10
                           10
Faceted navigation
              Why we need that?
•   The search does not end on a (long) list of results

•   The result...
Faceted navigation
  How we do better?




                      11
                           11
Faceted navigation
              How we do better?


•   A set of navigation services: access, search, filter,
    similar,...
Browsing the data graph




                          12
                               12
Browsing the data graph




 MultiBeeBrowse exploits interconnected data ...
                                             ...
Browsing the data graph




                          13
                               13
Browsing the data graph




    ... to allow faceted navigation
                                      13
                 ...
Social Semantic
Collaborative Filtering




                          14
                               14
Social Semantic
Collaborative Filtering

Why do we need collaboration?

•   The bottom-line of acquiring knowledge: inform...
Social Semantic
Collaborative Filtering




                          15
                               15
Social Semantic
Collaborative Filtering

           How can that help?

•   Everyone classifies (filters) the information in...
Social Semantic
Collaborative Filtering




                          16
                               16
Social Semantic
Collaborative Filtering

             What do we got?

•   Knowledge “flows“ from the expert through the so...
Social Semantic
Collaborative Filtering




                          17
                               17
Social Semantic
Collaborative Filtering

        What problems can we
             encounter?

•   The horizon of a social...
Social Semantic
Collaborative Filtering




                          18
                               18
Social Semantic
Collaborative Filtering

           How to solve them?

•   Inference engine to suggest knowledge from the...
Social Semantic
Collaborative Filtering




                          19
                               19
Social Semantic
           Collaborative Filtering
 know
 s
include

bookmark




                                     19
...
Social Semantic
           Collaborative Filtering
 know
 s
include

bookmark




                                     19
...
Putting it all together




                          20
                               20
Putting it all together




                          20
                               20
Putting it all together
   user profile:
  user’s interests




                                                          ...
Putting it all together
   user profile:
  user’s interests



                             user profile:
                ...
Search and Browsing
 in e-Learning space




                       21
                            21
Search and Browsing
 in e-Learning space




                       21
                            21
Search and Browsing
 in e-Learning space




                       21
                            21
Search and Browsing
 in e-Learning space




                       21
                            21
Search and Browsing
 in e-Learning space


             Sebastian Ryszard Kruk
                eLearning Cluster
         ...
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Search and Browsing Cycle for Knowledge Discovery and Learning

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Search and Browsing Cycle for Knowledge Discovery and Learning

  1. 1. Search and Browsing Cycle for Knowledge Discovery and Learning Sebastian Ryszard Kruk sebastian.kruk@deri.org DERI, NUI Galway 1
  2. 2. Search and Browsing Cycle for Knowledge Discovery and Learning Sebastian Ryszard Kruk sebastian.kruk@deri.org DERI, NUI Galway 1
  3. 3. Take away message 2 2
  4. 4. Take away message • We search in different ways for different things 2 2
  5. 5. Take away message • We search in different ways for different things • Keyword search is not enough 2 2
  6. 6. Take away message • We search in different ways for different things • Keyword search is not enough • We create the knowledge by sharing our (search) experience 2 2
  7. 7. Outline • Motivation • How do people search • Search and Browsing life-cycle • Applying semantics and making use of social networks: • Keyword-based search • Faceted Navigation • Collaborative Filtering • Conclusions 3 3
  8. 8. Motivation 4
  9. 9. Motivation How to discover and integrate knowledge coming from both formal and informal sources? 4
  10. 10. Motivation How to share and interconnect knowledge among people? 4
  11. 11. How do people search? • Different user goals: 5 5
  12. 12. How do people search? • Different user goals: – Resource Seeking - the user wants to find a specific resource (e.g. lyrics of a song, a program to download, a map service etc.) 5 5
  13. 13. How do people search? • Different user goals: – Resource Seeking - the user wants to find a specific resource (e.g. lyrics of a song, a program to download, a map service etc.) – Navigational - the user is searching for a specific web site whose URL s/he forgot 5 5
  14. 14. How do people search? • Different user goals: – Resource Seeking - the user wants to find a specific resource (e.g. lyrics of a song, a program to download, a map service etc.) – Navigational - the user is searching for a specific web site whose URL s/he forgot – Informational - the user is looking for information about a topic s/he is interested in 5 5
  15. 15. Search and browsing 6 6
  16. 16. Search and browsing • Why? • Knowledge can be useful • Not everything is a useful knowledge 6 6
  17. 17. Search and browsing • Why? • Knowledge can be useful • Not everything is a useful knowledge • How? (Search and browsing actions) 6 6
  18. 18. Search and browsing • Why? • Knowledge can be useful • Not everything is a useful knowledge • How? (Search and browsing actions) – [REUSE] keyword-based search (resource seeking) 6 6
  19. 19. Search and browsing • Why? • Knowledge can be useful • Not everything is a useful knowledge • How? (Search and browsing actions) – [REUSE] keyword-based search (resource seeking) – [REDUCE] faceted navigation (navigational) 6 6
  20. 20. Search and browsing • Why? • Knowledge can be useful • Not everything is a useful knowledge • How? (Search and browsing actions) – [REUSE] keyword-based search (resource seeking) – [REDUCE] faceted navigation (navigational) – [RECYCLE] collaborative filtering (informational) 6 6
  21. 21. Keyword-based search Why is it not enough? 7 7
  22. 22. Keyword-based search Why is it not enough? • Too many results (low precision) • One needs to specify the exact keyword (low recall) • How to distinguish between: Python and python? (high fall-out) 7 7
  23. 23. Keyword-based search How we can improve? 8 8
  24. 24. Keyword-based search How we can improve? • Disambiguation through a context • Long-term: user’s interests, engine type • Short-term: user’s goal, location, time • Query • Query refinement 8 8
  25. 25. Keyword-based search What’s next? 9 9
  26. 26. Keyword-based search What’s next? • “Tell me why” button and the transcript of refinement process • Continue to faceted navigation 9 9
  27. 27. Faceted navigation Why we need that? 10 10
  28. 28. Faceted navigation Why we need that? • The search does not end on a (long) list of results • The results are not a list (!) but a graph • „Lost in hyper-space” • A need for unified UI and services for filter/narrow and browse/expand services • Share browsing experience – navigate collaboratively 10 10
  29. 29. Faceted navigation How we do better? 11 11
  30. 30. Faceted navigation How we do better? • A set of navigation services: access, search, filter, similar, browse, and combine • Auxiliary services: meta, context, and statistics • Zoom-able, adaptable, and accessible user interface • Engage users in collaborative browsing 11 11
  31. 31. Browsing the data graph 12 12
  32. 32. Browsing the data graph MultiBeeBrowse exploits interconnected data ... 12 12
  33. 33. Browsing the data graph 13 13
  34. 34. Browsing the data graph ... to allow faceted navigation 13 13
  35. 35. Social Semantic Collaborative Filtering 14 14
  36. 36. Social Semantic Collaborative Filtering Why do we need collaboration? • The bottom-line of acquiring knowledge: informal communication (“word of mouth”) 14 14
  37. 37. Social Semantic Collaborative Filtering 15 15
  38. 38. Social Semantic Collaborative Filtering How can that help? • Everyone classifies (filters) the information in bookmark folders (user-oriented taxonomy) • Peers share (collaborate over) the information (community- driven taxonomy) 15 15
  39. 39. Social Semantic Collaborative Filtering 16 16
  40. 40. Social Semantic Collaborative Filtering What do we got? • Knowledge “flows“ from the expert through the social network to the user • Systems amass a lot of information on user/community profile (context) 16 16
  41. 41. Social Semantic Collaborative Filtering 17 17
  42. 42. Social Semantic Collaborative Filtering What problems can we encounter? • The horizon of a social network (2-3 degrees of separation) • How to handle fine-grained information (blogs, wikis, etc.) 17 17
  43. 43. Social Semantic Collaborative Filtering 18 18
  44. 44. Social Semantic Collaborative Filtering How to solve them? • Inference engine to suggest knowledge from the outskirts of the social network • Support for Semantically Interlinked Online Communities (SIOC) metadata 18 18
  45. 45. Social Semantic Collaborative Filtering 19 19
  46. 46. Social Semantic Collaborative Filtering know s include bookmark 19 19
  47. 47. Social Semantic Collaborative Filtering know s include bookmark 19 19
  48. 48. Putting it all together 20 20
  49. 49. Putting it all together 20 20
  50. 50. Putting it all together user profile: user’s interests refine search results 20 filter, record, annotate, and share results and actions 20
  51. 51. Putting it all together user profile: user’s interests user profile: recent actions refine filter, record, search results annotate, and share results re-call shared actions 20 filter, record, annotate, and share results and actions 20
  52. 52. Search and Browsing in e-Learning space 21 21
  53. 53. Search and Browsing in e-Learning space 21 21
  54. 54. Search and Browsing in e-Learning space 21 21
  55. 55. Search and Browsing in e-Learning space 21 21
  56. 56. Search and Browsing in e-Learning space Sebastian Ryszard Kruk eLearning Cluster DERI, NUI Galway sebastian.kruk@deri.org http://elite.deri.org/ http://www.corrib.org/ 21 21

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