Media Sharing on Urban Transport

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UCL-CS MobiSys

Divertissement et humour Business

Media Sharing based on Colocation Prediction in Urban Transport ,[object Object],[object Object],[object Object]

Talk Outline ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]

Isn't this already possible? ,[object Object],[object Object],[object Object]

Main Challenges ,[object Object],[object Object],[object Object],[object Object]

Approach: Colocation Prediction ,[object Object],[object Object],[object Object],[object Object],[object Object]

Selection Process Rock Metal Blues Alice Bob Carol Daniel

Selection Process Rock Blues Country Pop Jazz Classical Rock? Metal? Blues? Alice Bob Carol Daniel Pop Rock

Selection Process Rock Blues Country Pop Rock Pop Jazz Classical Rock? Metal? Blues? Alice Bob Daniel Carol

Selection Process: Bob or Carol? Rock Blues Country Pop Rock Bob Carol Carol may offer more appropriate content. Transfer completion is paramount. Therefore: choose host with longest remaining colocation time: remaining = predictedLength(host,time) – colocationStart(host)‏ Should a transfer be initiated if remaining is very small?

Approach: Temporal Mean ,[object Object],[object Object],0-4 4-8 8-12 12-16 16-20 20-24 3.5 5 25.7 14.3 2.8 18 15.9 Global Hour of day Overall 23 10 - 13.8 - 12.4

Approach: Temporal Mean ,[object Object],0-4 4-8 8-12 12-16 16-20 20-24 3.5 5 25.7 14.3 2.8 18 15.9 Global Bob Hour of day Overall 12 - - - - 12 -

Approach: Temporal Mean ,[object Object],[object Object],[object Object],0-4 4-8 8-12 12-16 16-20 20-24 3.5 5 25.7 14.3 2.8 18 15.9 Global Bob Hour of day Overall 13 7 - 13.8 - 12.4 -

Implementation ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]

Urban Transport Dataset ,[object Object],[object Object],[object Object],[object Object],[object Object]

Dataset processing ,[object Object],[object Object],[object Object],[object Object],[object Object]

Dataset processing ,[object Object],[object Object],[object Object],[object Object],8.30 Alice in 8.45 Bob in 9.30 Alice out 9.45 Bob out Elephant & Castle Lambeth North Waterloo Embankment Charing Cross Piccadillly Circus

Content Modelling ,[object Object],[object Object],[object Object]

Library Creation ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]

Library Creation: track popularity Distribution of proportional track popularity from artists last.fm

Results: Selection Methods ,[object Object],[object Object],[object Object]

Advertising Policy ,[object Object],[object Object],[object Object],[object Object]

Results: Advertising Policy Using data from the Reality Mining project lasting a whole year.

Related Work ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]

Conclusions ,[object Object],[object Object],[object Object],[object Object]

Questions? http://www.cs.ucl.ac.uk/staff/l.mcnamara

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Media Sharing on Urban Transport

8. Selection Process Rock Metal Blues Alice Bob Carol Daniel

9. Selection Process Rock Blues Country Pop Jazz Classical Rock? Metal? Blues? Alice Bob Carol Daniel Pop Rock

10. Selection Process Rock Blues Country Pop Rock Pop Jazz Classical Rock? Metal? Blues? Alice Bob Daniel Carol

11. Selection Process: Bob or Carol? Rock Blues Country Pop Rock Bob Carol Carol may offer more appropriate content. Transfer completion is paramount. Therefore: choose host with longest remaining colocation time: remaining = predictedLength(host,time) – colocationStart(host)‏ Should a transfer be initiated if remaining is very small?

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23. Library Creation: track popularity Distribution of proportional track popularity from artists last.fm