Social tagging networks stn leveraging context and social networks
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Social Tagging Networks (STN) Leveraging context and social networks. Johann STAN 1,2, Sonia LAJMI 3, PR. Pierre MARET 1, DR. Elod EGYED-ZSIGMOND 3 (PHD Candidate , 1st Year) 1 Alcatel-Lucent Bell Labs France – [email protected]

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Social Tagging Networks (STN) Leveraging context and social networks

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Social tagging networks stn leveraging context and social networks

Social Tagging Networks (STN)Leveraging context and social networks

Johann STAN1,2, Sonia LAJMI3,PR.Pierre MARET1, DR.Elod EGYED-ZSIGMOND3

(PHD Candidate, 1st Year)

1Alcatel-Lucent Bell Labs France – [email protected]

2Laboratoire Hubert-Curien, Université de Lyon, Saint-Etienne – [email protected]

3LIRIS CNRS Insa de Lyon, Université de Lyon [email protected]


Motivations

Motivations

  • There is a need to share photos and to retrieve them

    • Photo album creation

    • Selection of photos according to a given criteria

  • A photo with a name like DSC_0032.jpg is very difficult to retrieve

  • Efficient photo tagging is the main ground for retrieval and sharing

    • Facebook 10 million photos

    • Flickr 2 billion photos and 54 million users


Motivations1

Motivations

  • People take more and more photos with mobile devices

  • Mobile devices have a lot of sensors

    • Location, network, accelerometer, …

  • A photo is a meta-data for an event (and not THE event)

    • A trip in a foreign country, a party, a wedding, a dinner, a conference, ….


State of the art the use of semantics in tagging models

State of the ArtThe use of semantics in Tagging Models


Definition of main concepts

Definition of main concepts

  • Tagging Models

    • Structured according to description schemas

    • Completely free

    • Between the two

  • Tagging Activity

    • Automatic (GEO – Twitter)

    • Semi-automatic (MobileSocialNetwork)

    • Manual

  • Assistance in tagging

    • Keyword recommendation

    • Similar photo recommendation

    • Description schema recommendation


  • Geo twitter

    GEO-Twitter

    • Twitter updates are tagged with

      • #GEO: location

      • #Social: your social environment

      • The corresponding template is :

    Number of Bluetooth peers

    Cell Tower Identifier

    hasValue

    Automatic Tags

    hasValue

    Social environment

    Location

    hasTagType

    hasTagType

    isTemplate

    Ressource

    Twitter status message

    isA

    Template[i]


    Geo twitter implementation

    GEO-Twitter implementation

    • Create local communities

    • Location-related information

    • What is going on in in my neighborhood?


    Tagging model for social interactions

    Tagging Model for Social Interactions

    Automatic Tags

    Manual Tags

    • Interactions by phone are tagged with:

      • #GEO: location

      • #Social: your social environment

      • #Social Category of the correspondent

      • #Subject / Event in the conversation

      • #Emotional state of the correspondent

    isA

    Template[j]

    isTemplate

    Event

    Subject

    Social Category

    hasTagType

    Emotional State

    hasTagType

    hasTagType

    Social Environment

    hasTagType

    hasTagType

    Location

    hasTagType

    Interaction


    Social interaction analysis

    Social Interaction Analysis

    Guide the user to explicitly specify the content, context and/or quality of an interaction.

    10 | Social Communications | October 2008


    The role of context in semantic tagging

    The role of context in semantic tagging

    • Related Work deals wih 2 types of context:

      • The context of the photo taking moment

        • PhotoMap, ZoneTag, MMM Image Gallery

      • The context of tagging

        • M. Naaman et coll. 2005

        • B. Shevade, H. Sundaram 2007

        • B. Elliott et Z.M. Özsoyoglu2008


    Towards semantic tagging models

    Towards Semantic Tagging Models

    SCOT (Social Semantic Cloud of Tags) [4]

    • Describes the structure and semantics of tagging data, enables social interoperability of tagging data among heterogeneous sources

    • A combination of SCOT, FOAF and Dublin Core to describe tagging activity


    Towards semantic tagging models1

    Towards Semantic Tagging Models

    MOAT (Meaning of a Tag)

    MOAT (Meaning of a Tag)

    (2008, [5])

    • Meaning of a Tag depends on context

    • Introduction of the social aspects of tagging (community, sharing, …)


    Conclusion of semantic tagging models

    Conclusion of Semantic Tagging Models

    • The need for a semantic layer has been clearly identified (similar trend in user modeling community)

    • Several attemps to federate tag ontologies

    • Emerging concepts in tagging models

      • The role of context

      • Social networking and collaborative aspects

    • The issue of how to guide the user in tagging activity

    • User will not tag unless the system immediatly shows a pertinent concept, question…(the user must feel the immediate benefit of tagging)

      • What are the most pertinent concepts to tag according to my context?

      • How can i leverage my social network to increase tagging experience?

    • User Interface Challenge (very important)


    Better and richer annotation of persons on a picture work with sonia lajmi

    Better and richer annotation of persons on a pictureWork with Sonia LAJMI


    Scenario

    Scenario

    • 25/10/2007: Carole’s birthday

    • She invites collegues and close friends to a night club

    • Bernart takes a photo of the event

    • Marco meets Carole and asks Bernart to share the photo with him

    • The photo is also sent to Alice, Amélie and Carol


    Social tagging networks stn leveraging context and social networks

    Alice

    Amélie

    Carole

    What: ?

    Who: ?

    When: 25/12/2007

    Where: ?

    What: Carole’s birthday

    Who/relation: Carole dance

    With Alice

    Amélie dances with Boris

    Activity: Dance Hip Hop

    Where: Nightclub Berlin

    What: Christmas evening

    Where/relation: Beautiful girls dance

    Activité: dance Hip Hop

    Où: Nightclub Berlin

    Witnesses

    Amis de Alice

    What: party

    Where/relation: Alice dances with a girl

    Activity: dance

    Where: public place

    Carole’s friends

    Amelie’s friends

    What: Carole’s friends

    Where/relation: Carole dances with Alice

    Activity: dance

    Where: public place


    Social tagging networks stn leveraging context and social networks

    Photo

    Interpret

    Geographic

    Information

    Infer social

    relationships

    Publication

    Comment1: y r endow majdouline

    Comment2: kiss

    Comment3:

    Publication

    Personalized

    tagging

    Infer appropriate

    tags

    WS

    User Feedback

    User Context

    Knowledge

    Geographic

    Information

    ConceptNet

    User Calendar

    Social Networks

    Services Web

    Tagger


    Social relationship inference

    Social Relationship Inference

    Galery

    Scene

    night club party

    dc:identifier

    ‘http://www... ‘

    dc:type

    ‘Bernart’

    ‘Image ‘

    foaf:name

    dc:author

    ‘Bernart’

    foaf:Person

    foaf:phone

    displayedBy

    ‘0049636310166’

    foaf:Person

    foaf:Person

    ref: knowsInPassing

    foaf:Person

    hasRole

    foaf:phone

    foaf:Person

    foaf:phone

    foaf:name

    ‘photograph’

    foaf:phone

    ‘0049621110100’

    ‘0049636310166’

    ‘0033628310142’

    foaf:name

    post

    ‘Marco’

    ‘Carole’

    ‘y r endow Carole’

    Marco


    Extension of foaf profiles for social relationship categories

    Extension of FOAF profiles for social relationship categories


    Extension of foaf profiles for social networking

    Extension of FOAF profiles for social networking

    Event: Conference Meeting

    Picture with collegues from

    different countries

    • Social relationships differ according to the role of the person (witness, tagger, actor, viewer…)


    Heuristics to increase search in the foaf network

    Heuristics to increase search in the FOAF network

    • Association of context and social network categories

      • When at Work, the most probable SNC is the « Professional »

      • When at Home, the most probable SNC is the « Home »

      • ….


    Conclusion

    Conclusion

    • Overview of the application of semantic technologies in tagging

    • There is a need to leverage context and social networks to improve the tagging experience

    • There is a need to provide a mechanism that guides the user in the tagging activity (tagging templates or schemas)

    • The integration of social network, semantics and content annotation has the potential to revolutionize web interaction

    • This leads towards decentralized, but strongly interconnected communities


    Key references

    Key References

    • [1] G. Thomas, “Ontology of folksonomy: A mashup of apples and oranges,” Intl Journal on Semantic Web and Information Systems, 2007.

    • [2] N. Richard , “Tag Ontology,” http://holygoat.co.uk/owl/redwood/0.1/tags, 2005.

    • [3] J.G. Breslin and U. Bojars: “sioc-project.org | Semantically-Interlinked Online Communities.”

    • [4] Hak Lae Kim, J. Breslin, S.K. Yang, H.G. Kim: Social Semantic Cloud of Tag: Semantic Model for Social Tagging. KES-AMSTA: 83-92

    • [5] Alexandre Passant, Philippe Laublet: Combining Structure and Semantics for Ontology-Based Corporate Wikis. BIS 2008: 58-69

    • [6] Jacques Calmet, Pierre Maret, Régine Endsuleit: Agent Oriented Abstraction.

    • Royal Academy of Sciences Journal. Special Issue on Symbolic Computation in Logic and Artificial Intelligence. Vol.98 (1-2). pp.77-84. 2004


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