0. Bridging Recommendation and Adaptation GAF-Twittomender compliance case-study
John Hannon, Evgeny Knutov, Paul De Bra,
Mykola Pechenizkiy, Barry Smyth, Kevin McCarthy

1. Agenda AH systems evolution, GAF
AH process modelling and GAF building blocks
GAF-RecSys compliance
Twittomender highlights
Twittomender case-study
Lessons learned
Further Twittomender extension
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2. AH Systems and GAF Generalize AHS functionality in GAF reference model
(incl. systems which are not labelled as AH, e.g. RecSys)
Enhance GAF layered structure with the process
Enrich GAF with new approaches, techniques
say about system analysis, evaluation as one of the major Reference Model’s goals
including those systems which are not labelled as AH systems
RecSys can be viewed as being AH systems
show the model and do the case-study
1990 – 1998->2002 -> now
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3. Adaptation process modeling
Classic loop user modeling - adaptation
Generic Adaptivity Model
diversity of adaptation process modelling approaches, representations and models
GOMAWE
Munich Model: Lifecycle of Adaptation
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4. Classification of AH methods and techniques; adaptation process
Classification of AH methods and techniques integrated with adaptation process
Basis for the AHS layered structure
original AHS classification, and adaptation process insights
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5. GAF layered model
GAF aligns the order of the layers in the system according to the classification of AH methods and techniques
Rotate layered structure of GAF and match with adaptation process flowcharts
GAF layered structure building blocks
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6. GAF ‘sequence chart’ – RecSys compliance
present different recommendation approaches (explain an example of a hybrid recommender)
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7. Having trouble finding people to follow on Twitter?
Syncing a users account and producing followee recommendations through a range of collaborative (3) and content-based (4) strategies
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8. Twittomender architecture
Client-Server architecture
Build on top of Twitter API and Lucene (full features text search engine)
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9. GAF – Twittomender compliance
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10. GAF – Twittomender compliance (cont.)
Resource Model – Tweets (via Twitter API)
Goal Model – Twitter Profile login / Search query
User Model – Twittomender User profiler
Domain Model – Lucene index of users’ tweets
Group Model – Collaborative twitter profile (followers)
Application Model – Twittomender framework
Adaptation Model – Retrieval module (Lucene)
No Twittomender Contextual info
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11. Lessons Learned
Helped to identify Twittomender missing parts / extension possibilities
Recommendation of resources of a different nature
(elaborate) User Modelling
Contextualization
Further Twittomender Extensions (UM interoperability)
users are considered as concepts, and AH wise it is considered whether the user as a concept is suitable to follow
your profile interest is matched on on the other users index of tweets, so that you get recommendations based on the user-concept suitability
UM mapping from other systems without realizing the actual UM (e.g. modelling interest, etc.)
!!! indicate missing parts (e.g Context of tweets, user context) – however model considers context of a different type
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12. UM interoperability in Twittomender
UM interoperability use-case (sharing Google web history and Twittomender personal user index)
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13. (to be continued) Thanks! Questions?
and
Questions?
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