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Searching The Social Web
Searching The Social Web
Searching The Social Web
Searching The Social Web
Searching The Social Web
Searching The Social Web
Searching The Social Web
Searching The Social Web
Searching The Social Web
Searching The Social Web
Searching The Social Web
Searching The Social Web
Searching The Social Web
Searching The Social Web
Searching The Social Web
Searching The Social Web
Searching The Social Web
Searching The Social Web
Searching The Social Web
Searching The Social Web
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Searching The Social Web

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A talk on social search as implemented in Delver, presented in IBM-HRL IR technologies/social search seminar, 16/12/2008.

A talk on social search as implemented in Delver, presented in IBM-HRL IR technologies/social search seminar, 16/12/2008.

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  • Talk in IBM-HRL Information Retrieval seminar 16/12/2008
  • Transcript

    • 1. Searching the Social Web The Challenges of Socially-Connected Search IR Leadership Seminar 2008 / Ofer Egozi
    • 2. The problem… What to choose? Whom to trust??...
    • 3. … The solution? What to choose? Whom to trust??...
    • 4.
      • Leveraging the Social Graph in web search
        • Focused crawling
        • Personalized ranking
      • Delver is a first-mover
      The solution? Socially- connected search: What to choose? Who to trust??...
    • 5.
      • Trusted results
        • Friends qualify content/sources
        • Potential contact in reach
        • Spam is inherently low
      • Reasoning over results
        • Ranking is transparent
        • Easier to assess relevance
      • Network discovery
        • Experts in my network
        • Serendipity
      The solution? Socially- connected search: What to choose? Who to trust??...
    • 6. Outline
      • Approaches to Social Search
      • The Social Graph
      • Graph-Related Challenges
      • Search-Related Challenges
    • 7. Humans in the loop
      • Search = crawl + index + rank + query
      • Crawling (Dmoz, Mahalo)
      • Indexing (del.icio.us, Flickr)
      • Querying (ChaCha)
      • Ranking – that’s what we’ll discuss…
    • 8. A Taxonomy of Social Search Aggregated Personalized Network-based Behavior- based ? ?
    • 9. The Social Graph
      • A directed, cyclic graph
        • Nodes are people (identities)
        • Edges are relations between them
      • Large portion is public on social networks
      • A lot isn’t – cellular, email, non-digital
      • Emerging web standards
        • OpenID/hCard – identifier/identity
        • Contact APIs/PoCo/XFN – private/public contact lists
        • FB Connect – a full proprietary framework
    • 10. Social Graph in Research
      • Extraction from interactions
        • Email (Van Alstyne et al. 2003), Chat (Tuulos & Tirri 2004), IM (Lang 2004)
      • Correlation with “physical”
        • Bluetooth contact (Mtibaa et al. 2008)
      • Security and Privacy
        • Shared knowledge authentication (Toomim et al. 2008)
        • Graph link privacy (Xu 2008), (Korolova et al. 2008)
      • Enhance IR ranking
        • Index friends browse history (Mislove et al. 2006)
        • Rank by author centrality (Kirchhoff et al. 2008)
        • Rerank by sampling network click-log (Das et al. 2008)
    • 11. So first we need to draw the graph…
    • 12. Social Graph - challenges
      • Social graph nodes
        • Identities/relations across networks
      Joe friend-of follows friend-of follows Joe JJ123 Joey
    • 13.  
    • 14. Social Graph - challenges
      • Social graph nodes
        • Identities/relations across networks
        • Identity impersonation
        • Non-individual identities (groups, shared authorship…)
        • Privacy is an issue, even with public data
      • Social graph edges
        • Relation “strength” not exposed
        • Super nodes may dominate results
        • “ Politeness” relations are not filtered out
        • Automatic generation – double-edged sword
      Joe friend-of follows friend-of follows Joe JJ123 Joey
    • 15. So now we’ve mapped the social graph… … and attached each node with its content…
    • 16. … can we finally go fetch?
    • 17. S-C Search - challenges
      • Must build a search engine…
        • Store graph, attach content to nodes
        • Reranking will not do, this is the long tail
    • 18. Not in Google’s / Yahoo!’s top-1000!… (dominated by authorities)
    • 19. S-C Search - challenges
      • Must build a search engine…
        • Store graph, attach content to nodes
        • Reranking will not do, this is the long tail
        • Scale well, including graph functions
      • Personalized graph-based rank
        • Integrate content-based with static ranking
        • Use web graph structure, like PageRank etc.
        • Network is egocentric , unlike PageRank
    • 20. Socially-Connected Search
      • What are the enablers?
        • Social networks
        • Users’ content boom
      • What can be achieved?
        • Search-based access to network content
        • Trusted and transparent social ranking
      • What are the challenges?
        • Fragmented social graph
        • Personal-network ranking
      Thank you! http://www.delver.com

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