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You Are What You Tag. Yi-Ching (Janet) Huang Chia-Chuan (Evelyn) Hung Jane Yung-jen Hsu From National Taiwan University 2008/03/26. Tagging-based profile Objective profile Semantic relationship between tags. Outline. Social Media Website. blogs. musics. bookmarks. movies. maps.

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You Are What You Tag


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    Presentation Transcript
    1. You Are What You Tag Yi-Ching (Janet) Huang Chia-Chuan (Evelyn) Hung Jane Yung-jen Hsu From National Taiwan University 2008/03/26

    2. Tagging-based profile Objective profile Semantic relationship between tags Outline

    3. Social Media Website

    4. blogs musics bookmarks movies maps photos shrek MRT lord of rings ntu opera jazz classical java rock ai xml school ocean life travel food night-market cat

    5. Things I have reflect what I know, and what I am interested in Social Media -> Profile Japan drama Cats musical Visualization tools social networks graph social networks Visualization networks comic Japan Namie

    6. Content vs. Tag Analysis

    7. You Are What You Tag programming coffee music cat movie musical comic ajax Japan rabbit java SFO Taiwan dance xml jazz map travel JavaScript R&B

    8. Social Bookmarking Data My bookmarks My friends’ bookmarks cats ajax musical xml rdf dance java comic music movie coffee star

    9. Tripartite Graph 0.3 0.57 0.46 routing Japan 0.84 0.24 java 0.63 travel …… tagged on … … own

    10. Weighted Tag Profile Obtain a set of tags ordered by its weight to represent this person Tag weight The average tag importance (over document) routing Japan travel java …… tagged on own … …

    11. Tag Capability How much a tag can represent this document Tagging order The first tag is the most relevant Tagging popularity How many people also tag this document with this tag routing Japan travel java …… tagged on … … own

    12. map jazz guide R&B pop Japan Taiwan animal travel rdf xml java kitty cats rss javaScript dance objective musical objective subjective

    13. Tags from Other People For any document in my collection, it may be tagged by other people map Japan map travel Japan Japan

    14. Objective Profiling 0.13 0.28 0.43 travel routing Japan 0.92 0.35 0.57 map java …… rdf javaScript

    15. Different Viewpoints travel Japan Thailand movie rdf cats comic musical Japan ajax R&B Visuali-zation movie jazz java love theme cats musical dance Japan java xml cats Taiwan dance comic map programming JavaScript JavaScript dance Taiwan map musical travel jazz pop R&B rdf java personal social global subjective objective

    16. Profile from Three Views personal view Others say I am… ? social view global view

    17. Are They Alike?

    18. Pre-processing image flash photo color design flex tagging art javascript research ajax social reinforcement

    19. Relationship between Tags icon image flash photo color graph paint flex tagging art javascript research design ajax

    20. Tag-based Co-occurrence Assumption: the more frequent two tags co-occur on the same documents, the more relevant two tags are A B

    21. Tag Semantic Relationship icon image photo color graph paint art design 1/5 = 0.25

    22. Tag Concept icon image concept image flash photo color graph paint flex tagging art javascript research design ajax Semantic relation (WordNet) Semantic relation (ConceptNet)

    23. Concept-based Co-occurrence icon image concept image flash photo color graph paint flex tagging 3/8 = 0.375 art javascript research art concept design ajax

    24. Profile with Semantic Relationship personal view Others say I am… ? social view global view

    25. Experiment of Data A user’s bookmark collection (from del.icio.us) 351 bookmark items 148 distinct tags 160,000 users bookmarked one of these items Visual tool Vizster (Heer 2005)

    26. Result of Tag Relationship

    27. Tagging-based profile Profile a person from tags Profile from different views personal, social, global Tag semantic relationship More complete profile Conclusion

    28. Thanks for your attention 

    29. 1 2 3 4

    30. Tagging Analysis 0.3 0.57 0.46 routing Japan 0.84 0.24 travel java …… tagged on Tag vs. Person Tag vs. Content … … own

    31. Results of Three Viewpoints My docs

    32. Procedure of semantic relationship analysis

    33. Relationship between tags can Reflect how I think The structure of my knowledge Japan cats cats musical travel travel Taiwan Japan Taiwan musical Relationship between tags

    34. All Aspects Are You Japan cats map jazz Japan map JavaScript musical R&B travel Japan rdf java movie Thailand pop Japan R&B musical comic cats rdf jazz dance ajax cats visualization java love theme dance Taiwan dance map java xml JavaScript JavaScript musical pop subjective profile objective profile

    35. You Are What You Tag

    36. art design ? visual Easy to miss tag ?

    37. design art layout web color visual tutorial Easy to miss tags ? ……….. ……….. ……….. ……….. ? ?

    38. Social reinforcement image flash photo color design flex tagging art javascript research ajax social reinforcement

    39. Tag relative co-occurrence

    40. How people think…

    41. Tag relationship Concept-based relative co-occurrence Social reinforcement More complete profile Conclusion

    42. A Tripartite Graph (Mika, 2005) T = A × C × I A: actors C: concepts I: instances H(T)=(V, E) V = A∪C∪I E = { { a,c,i } | (a,c,i) belongs to T } Evelyn Joe URL_6 … … java URL_5 … … travel … … URL_8 Peter Janet comic Data Modeling

    43. A Tuple of Data 2006/10/10 java, programming, research tagged on Evelyn http://xxxx.com … … own

    44. Give each tag a weight as its importance Tags vs. Contents The capability of a tag for representing the content. Tags vs. Profile The strength of a tag for representing a person Tags vs. Profile vs. Time The changes of the tags over time Tag Analysis

    45. Tags vs. Contents y=exp(x) 0.75 0.65 0.80 0. 54 0.61 0. 62 0.80 programming 0.69 java research 0.9 0.74 0.83 0.67 0.33 0.67 0. 75 0.91 2.2 0.79 1.16 0. 54 3.8 0.79 http://xxxx.com … …

    46. Tags vs. Profile 0.52 0.43 URL_6 URL_5 … … … … 0.79 0.95 3.5 4.0 URL_2 … … URL_3 … … programming 0.78 3.8 0.7 0.6 URL_4 … … 0.67 2.7 3.54 java research URL_1 … … 0.89 Evelyn 1.1 6.52 2.44 URL_9 … … 0.4 1.9 … … URL_7 … … 0.83 URL_8 0.9

    47. Tag vs. Content Tag vs. Person (Personal) Tag vs. Person (Social) Equations