Search and Browsing Cycle for Knowledge Discovery and Learning

Loading...

Flash Player 9 (or above) is needed to view presentations.
We have detected that you do not have it on your computer. To install it, go here.

0 comments

Post a comment

    Post a comment
    Embed Video
    Edit your comment Cancel

    6 Favorites

    Search and Browsing Cycle for Knowledge Discovery and Learning - Presentation Transcript

    1. Search and Browsing Cycle for Knowledge Discovery and Learning Sebastian Ryszard Kruk sebastian.kruk@deri.org DERI, NUI Galway 1
    2. Search and Browsing Cycle for Knowledge Discovery and Learning Sebastian Ryszard Kruk sebastian.kruk@deri.org DERI, NUI Galway 1
    3. Take away message 2 2
    4. Take away message • We search in different ways for different things 2 2
    5. Take away message • We search in different ways for different things • Keyword search is not enough 2 2
    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. 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. Motivation 4
    9. Motivation How to discover and integrate knowledge coming from both formal and informal sources? 4
    10. Motivation How to share and interconnect knowledge among people? 4
    11. How do people search? • Different user goals: 5 5
    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. 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. 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. Search and browsing 6 6
    16. Search and browsing • Why? • Knowledge can be useful • Not everything is a useful knowledge 6 6
    17. Search and browsing • Why? • Knowledge can be useful • Not everything is a useful knowledge • How? (Search and browsing actions) 6 6
    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. 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. 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. Keyword-based search Why is it not enough? 7 7
    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. Keyword-based search How we can improve? 8 8
    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. Keyword-based search What’s next? 9 9
    26. Keyword-based search What’s next? • “Tell me why” button and the transcript of refinement process • Continue to faceted navigation 9 9
    27. Faceted navigation Why we need that? 10 10
    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. Faceted navigation How we do better? 11 11
    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. Browsing the data graph 12 12
    32. Browsing the data graph MultiBeeBrowse exploits interconnected data ... 12 12
    33. Browsing the data graph 13 13
    34. Browsing the data graph ... to allow faceted navigation 13 13
    35. Social Semantic Collaborative Filtering 14 14
    36. Social Semantic Collaborative Filtering Why do we need collaboration? • The bottom-line of acquiring knowledge: informal communication (“word of mouth”) 14 14
    37. Social Semantic Collaborative Filtering 15 15
    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. Social Semantic Collaborative Filtering 16 16
    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. Social Semantic Collaborative Filtering 17 17
    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. Social Semantic Collaborative Filtering 18 18
    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. Social Semantic Collaborative Filtering 19 19
    46. Social Semantic Collaborative Filtering know s include bookmark 19 19
    47. Social Semantic Collaborative Filtering know s include bookmark 19 19
    48. Putting it all together 20 20
    49. Putting it all together 20 20
    50. Putting it all together user profile: user’s interests refine search results 20 filter, record, annotate, and share results and actions 20
    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. Search and Browsing in e-Learning space 21 21
    53. Search and Browsing in e-Learning space 21 21
    54. Search and Browsing in e-Learning space 21 21
    55. Search and Browsing in e-Learning space 21 21
    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

    + Sebastian KrukSebastian Kruk, 3 years ago

    custom

    2043 views, 6 favs, 0 embeds more stats

    Slides from the presentation I gave at 5th Annual C more

    More info about this document

    CC Attribution-NonCommercial LicenseCC Attribution-NonCommercial License

    Go to text version

    • Total Views 2043
      • 2043 on SlideShare
      • 0 from embeds
    • Comments 0
    • Favorites 6
    • Downloads 94
    Most viewed embeds

    more

    All embeds

    less

    Flagged as inappropriate Flag as inappropriate
    Flag as inappropriate

    Select your reason for flagging this presentation as inappropriate. If needed, use the feedback form to let us know more details.

    Cancel
    File a copyright complaint
    Having problems? Go to our helpdesk?

    Categories