Ubiquitous User Modeling in Recommender Syste In this work we aim at developing an abstract mediation mechanism that will allow upgrading the existing personalization systems by integrating user models from dif- ferent data sources(both users and service providers). This will facilitate obtainin more information about users and providing more accurate personalization services 2 Integration of User Models The principal architecture of the evolving ubiquitous user modeling platform is repre sented in Figure /. The core of the platform is the mediating mechanism that facili tates user modeling data sharing by translation and integration of user models. As each service provider stores partial user model according to its own format and repre entation, mediating mechanism is responsible for the following tasks 1. Mapping from specific services to a generic representation and vice versa. 2. Providing standard language/interface for user modeling data exchange 3. Maintaining user modeling semantic knowledge facilitating ad-hoc mapping User Modeling User Modeling Available knowledge/ knowledge bas user data requested/provided services) User Fig. 1. Principal architecture of ubiquitous user modeling platform We propose to cluster the data sources storing user models from similar domains in order to improve the integration task and minimize the communication overhead tied with it. Note that the structure of the clusters is highly dynamic, as they comprise user's devices(providing partial user models), whose availability is unstable When different data sources share a model related to the same domain(e. g, mod els from Amazon and BarnesAndNoble ), the integration of partial user models is per- formed using the mediator's domain knowledge. It should support identifying seman- tic relations between different concepts in the domain. For example, it should inte grate partial models from systems using different ontologies to model users prefer ences in the same domain. Thus, the mediator should be capable of resolving conflicts and ambiguities, and facilitate obtaining accurate and expressive user model. Another issue that should be tackled by the mediator is integrating partial models from different domains. For example, consider the repositories of books and DVDs stores. Although the domains are not identical, user's interest in a particular genre of books can be inferred from the DVDs model. This requires identifying the relationUbiquitous User Modeling in Recommender Systems 497 In this work we aim at developing an abstract mediation mechanism that will allow upgrading the existing personalization systems by integrating user models from dif￾ferent data sources (both users and service providers). This will facilitate obtaining more information about users and providing more accurate personalization services. 2 Integration of User Models The principal architecture of the evolving ubiquitous user modeling platform is repre￾sented in Figure 1. The core of the platform is the mediating mechanism that facili￾tates user modeling data sharing by translation and integration of user models. As each service provider stores partial user model according to its own format and repre￾sentation, mediating mechanism is responsible for the following tasks: 1. Mapping from specific services to a generic representation and vice versa. 2. Providing standard language/interface for user modeling data exchange. 3. Maintaining user modeling semantic knowledge facilitating ad-hoc mapping. Fig. 1. Principal architecture of ubiquitous user modeling platform We propose to cluster the data sources storing user models from similar domains in order to improve the integration task and minimize the communication overhead tied with it. Note that the structure of the clusters is highly dynamic, as they comprise user's devices (providing partial user models), whose availability is unstable. When different data sources share a model related to the same domain (e.g., mod￾els from Amazon and BarnesAndNoble), the integration of partial user models is per￾formed using the mediator's domain knowledge. It should support identifying seman￾tic relations between different concepts in the domain. For example, it should inte￾grate partial models from systems using different ontologies to model user's prefer￾ences in the same domain. Thus, the mediator should be capable of resolving conflicts and ambiguities, and facilitate obtaining accurate and expressive user model. Another issue that should be tackled by the mediator is integrating partial models from different domains. For example, consider the repositories of books and DVDs stores. Although the domains are not identical, user's interest in a particular genre of books can be inferred from the DVDs model. This requires identifying the relation￾Service B B UM Mediator Available user data Request for a service Required user data Past interactions (requested/provided services) User Modeling knowledge base User Modeling knowledge User Service A A