Extending your neighborhood-relationship-based recommendations using your personal web context
The people, documents, and other entities from a domain persons know, or are in other ways associated with, influence their decision making and the types of recommendations that serve them best. For example, recommending persons to meet in a conference or a paper to read from a digital library collection does not only depend on the task, interests, and skills of a user, but also on the persons and works they are already familiar with. In order for personalization services to reflect this dependency, extended user models that consider users' network of related domain entities in addition to other user characteristics, are required. Based on a unified context model, we present the Personal Web Context approach that models the typed relationships a user is involved in. Based on a Resource Network which can, for example, be built from the information collection and the associated meta data managed by a digital library, domain-specific rules are used to suggest valuable extensions of this "neighborhood" of a user. Such work can form the basis for new types of digital library services.