Context Ontologies for Recommending from the Social Web Eoin Hurrell and Alan Smeaton.
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Transcript of Context Ontologies for Recommending from the Social Web Eoin Hurrell and Alan Smeaton.
Context Ontologies for
Recommending from the Social Web
Eoin Hurrell and Alan Smeaton
“Nothing is Written in Stone”
Eoin Hurrell and Alan Smeaton
Contextual Recommendation: the here and now
Eoin Hurrell and Alan Smeaton
“Users: The nut between the screen
and the chair”
Eoin Hurrell and Alan Smeaton
Eoin Hurrell and Alan Smeaton
251,807 tweets7,390 users
src: https://twitter.com/logo
“There is more to Context than
Location”-Albrecht Schmidt
Eoin Hurrell and Alan Smeaton
(P. Ingwersen and K. Järvelin. 2005.)
Recommendations:Who to Follow
Eoin Hurrell and Alan Smeaton
I Tweet Therefore I Am
Eoin Hurrell and Alan Smeaton
Posts per hour (24 attributes)
Follower countFriends count
Listed count
Tweet (statuses) count
Favourite count
Are their tweets geo enabled?
Verified
Profile presentation (8 attributes)
61 Context AttributesProtected
Language Place info (8 attributes)
Name info (5 attributes)
Twitter client(s) used
image: http://crgondim.wordpress.com/2011/08/08/dando-uma-cara-pro-cara/
image: http://crgondim.wordpress.com/2011/08/08/dando-uma-cara-pro-cara/
530 SVMs, each built on individual users’
view of their 7,390 peersimage: http://www.epicentersoftware.com/genetrix/features/machine_learning_heuristics.htm
Results: Feature importance
varied greatly
Our top five features
Top average features for discriminating
Most selected features
People are more unique than task-level
context
Eoin Hurrell and Alan Smeaton