Relevance measures for the creation of groups in an annotation system

The MADCOW annotation system supports a notion of group, facilitating focused annotations with respect to a domain. In previous work, we adopted ontologies to represent knowledge about domains, thus allowing more refined annotations to a group, and discussed how the use of ontologies facilitates the formulation of semantically significant queries for retrieving annotations on specific topics. We now expand on previous results and study two new types of measures to identify matches between users’ interests and groups: Degree Centrality, developed for social networks to assess the quality of concepts in an ontology, and URL concordance, indicating the similarity of interests among users who annotate the same pages

Relevance measures for the creation of groups in an annotation system

The MADCOW annotation system supports a notion of group, facilitating focused annotations with respect to a domain. In previous work, we adopted ontologies to represent knowledge about domains, thus allowing more refined annotations to a group, and discussed how the use of ontologies facilitates the formulation of semantically significant queries for retrieving annotations on specific topics. We now expand on previous results and study two new types of measures to identify matches between users' interests and groups: Degree Centrality, developed for social networks to assess the quality of concepts in an ontology, and URL concordance, indicating the similarity of interests among users who annotate the same pages