Combination of DROOL rules and Protégé knowledge bases in the ONTO-H annotation tool

ONTO-H is a semi-automatic collaborative tool for the semantic annotation of documents, built as a Protégé 3.0 tab plug-in. Among its multiple functionalities aimed at easing the document annotation process, ONTO-H uses a rule-based system to create cascading annotations out from a single drag and drop operation from a part of a document into an already existing concept or instance of the domain ontology being used for annotation. It also gives support to the detection of name conflicts and instance duplications in the creation of the annotations. The rule system runs on top of the open source rule engine DROOLS and is connected to the domain ontology used for annotation by means of an ad-hoc programmed Java proxy

Fuzzy Group Models for Adaptation in Cooperative Information Retrieval Contexts

Cooperation in information retrieval contexts can be used to share query results inside groups of individuals with common objectives, provided that all of them are aware of each other. The strength of the social relationships between group members is in most cases a matter of comparative degree, and thus relationships can be modelled through fuzzy conceptual associations. These associations can then be used to implement personalized features, aimed at improving the interaction of the user with the query tool. In this paper, an approach to modelling imprecise relationships between users in the context of information retrieval is described, along with a concrete case study implemented as a wrapper of a conventional search engine, using a fuzzy database to store the model of the group members

The Role of Vague Categories in Semantic and Adaptive Web Interfaces

Current Semantic Web technologies provide a logic-based framework for the development of advanced, adaptive applications based on ontologies. But the experience in using them has shown that, in some cases, it would be convenient to extend its logic support to handle vagueness and imprecision in some way. In this paper, the role of vagueness in the description of Web user interface characteristics is addressed, from the viewpoint of the design of adaptive behaviors that are connected to such descriptions. Concretely, vague descriptions combined with quantified fuzzy rules and flexible connectors are described, and their usefulness is illustrated through preference modeling, filtering and adaptive linking scenarios