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Inter-Context Trust Bootstrapping for Mobile Content Sharing (daniele quercia) (stephen hailes & licia capra). U C L. What do I do?. Research @. what I research?. Reputation Systems for Mobiles. What’s that?. Example: antique markets. Problem: Visitors cannot see prices of everything!.

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U c l

Inter-Context Trust Bootstrappingfor Mobile Content Sharing(daniele quercia)(stephen hailes & licia capra)

UCL


U c l

What do I do?


U c l

Research @


U c l

what I research?


U c l

Reputation Systems for Mobiles


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What’s that?


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Example:antique markets


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Problem:Visitors cannotsee prices of everything!


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Solution:Sellers disseminate e-ads, and visitors collect them


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Problem: Sellers may disseminate irrelevant ads


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Proposal:


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They may keep track of which sellers sendirrelevant ads


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Daniele Quercia

Trust model on A:how A decideswhether to rely on Bto visit a stall


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Daniele Quercia

To decide whether to rely on B, A has to

set its initial trust in B


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  • 3 Existing Solutions

Daniele Quercia


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Daniele Quercia

  • 1. Fixed values

  • ( over-simplified)


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Daniele Quercia

  • 2. Recommendations

  • ( fake ones)


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  • 3. Similar contexts

  • ( universal ontology)

Daniele Quercia


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Daniele Quercia

Two cases: B is

1. unknown

2. partly known


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Daniele Quercia

  • 1. B is unknown


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Daniele Quercia

  • Popular way:

  • Trust propagation (transitivity)

C

?

A

B


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Daniele Quercia

  • Meant for the Web &

    Proved on “binary” ratings


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  • Algorithm rating

  • unrated trust relationships (needed)

Daniele Quercia

  • unrated nodes (chosen)

?

AB

AC

CB

1

2

C

1

2

?

A

B


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?

  • Idea:

    • 1. Similar nodes together

    • 2. Find function:

    • same ratings for rated nodes

    • similar ratings for neighbours


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Daniele Quercia

  • Tested on real data

  • (Advogato: > 55K user ratings)


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Daniele Quercia

  • 2. B is partly known


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Daniele Quercia

Popular way:

Inter-context Lifting 

Antiques

Coins

Chairs

Roman Coins

Greek Coins


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  • Idea: Users …

    • > Don’t share ontology

    • > Extract “features”

    • from their own ratings

Daniele Quercia


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  • Idea: Users …

    • > Don’t share ontology

    • > Extract “features”

    • from their own ratings

Daniele Quercia


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Daniele Quercia

  • How to extract?


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Daniele Quercia

  • Singular

    • Value

    • Decomposition


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  • Beauty: features

  • not user-specified

  • BUT learnt

Daniele Quercia


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  • Tested on simulation with real parameters

Daniele Quercia


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Daniele Quercia

  • Tested on Nokia 3230

  • Max: 3.2 ms !


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Daniele Quercia

  • What I’ve told you is on

  • “mobblog UCL” (google it)

  • under tag: “bootstrapping”


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Daniele Quercia


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Daniele Quercia

  • And User Privacy?


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Daniele Quercia

  • Private filtering

  • (Google for “mobblog private filtering”)


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Daniele Quercia

  • And Resource Discovery?


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Daniele Quercia

  • Folksonomy for mobiles 


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Daniele Quercia

  • And Attacks?


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Daniele Quercia

Further Research

(join mobblog !)


  • Login