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Context Ontologies for Recommending from the Social Web Eoin Hurrell and Alan Smeaton.

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Presentation on theme: "Context Ontologies for Recommending from the Social Web Eoin Hurrell and Alan Smeaton."— Presentation transcript:

1 Context Ontologies for Recommending from the Social Web Eoin Hurrell and Alan Smeaton

2 “Nothing is Written in Stone” Eoin Hurrell and Alan Smeaton

3 Contextual Recommendation: the here and now Eoin Hurrell and Alan Smeaton

4 “Users: The nut between the screen and the chair” Eoin Hurrell and Alan Smeaton

5 Twitter Eoin Hurrell and Alan Smeaton 251,807 tweets 7,390 users src: https://twitter.com/logo

6 “There is more to Context than Location” -Albrecht Schmidt Eoin Hurrell and Alan Smeaton

7 (P. Ingwersen and K. Järvelin. 2005.)

8 Recommendations: Who to Follow Eoin Hurrell and Alan Smeaton

9 I Tweet Therefore I Am Eoin Hurrell and Alan Smeaton Posts per hour (24 attributes) Follower count Friends count Listed count Tweet (statuses) count Favourite count Are their tweets geo enabled? Verified Profile presentation (8 attributes) 61 Context Attributes Protected Language Place info (8 attributes) Name info (5 attributes) Twitter client(s) used

10 image: http://crgondim.wordpress.com/2011/08/08/dando-uma-cara-pro-cara/

11

12 530 SVMs, each built on individual users’ view of their 7,390 peers image: http://www.epicentersoftware.com/genetrix/features/machine_learning_heuristics.htm

13 Results: Feature importance varied greatly Our top five features

14 Top average features for discriminating

15 Most selected features

16 People are more unique than task-level context Eoin Hurrell and Alan Smeaton

17 Thank You Eoin Hurrell Questions? Contact me at Eoin.Hurrell@computing.dcu.ie Ask me after! or


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