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User Modeling for Personalized Web-Based Systems 237
application
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Mediator 1
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Figure 8-8. Architecture and stages of the user model mediation, according to [8].
For the purpose of mediator, the user model is considered as an aggregation of partial
domain-related user models: UM = aggr(UM 1 , UM 2 ,...,UM k ). The domain-related user
model is then defined as an aggregation of domain-related user models built by applications
exploiting different personalization techniques: UM d = aggr(UM 1 d, UM 2 d,...UM n d ), where
UM t d denotes the partial UM referred to application domain d, built by an application
exploiting personalization technique t.
Authorse can therefore divide all applications, which could potentially provide helpful
partial user models into three distinct groups:
– applications from d that also exploit t,
– applications from d that exploit another technique t’,
– applications from another, relatively similar, domain d’ that also exploit t.
Applications are apriori organized in a hierarchical semantically demarcated structure, where
upper level of the hierarchy represents different application domains. The domains are
represented by the nodes of an undirected graph, where the weights of the edges reflect
the similarity between the respective domains. The bottom layer represents specific applications
within the domains, grouped according to the personalization techniques they
exploit.
The actual translation and aggregation of the acquired partial user models is driven by
a rich inter- and intra- domain knowledge base that allows for identification of commonalities
between partial user models.
Three distinct types of translations are defined:
– simple concatenation of partial user models.
– cross-technique translation [9] – for example from collaborative to content-based
movie recommender. The translation exploits a KB of movies data (e.g., genres,
directors and actors), which allows the mediator to generalize a set of collaborative
ratings into the content-based user model, containing a list of genres, directors and
actors liked/disliked by the user.