Knowledge-based semantic annotation and retrieval of multimedia content

aceMedia is a 4 year EC part-funded FP6 Integrated Project, ending in December 2007. The project has developed tools to enable users to manage and share both personal and purchased content across PC, STB and mobile platforms. Knowledge-based analysis and ontologies have been successfully exploited in an end-to-end system to enable automated semantic annotation and retrieval of multimedia content. The paper briefly describes the objectives of aceMedia and the application of knowledge-based analysis in the project

Automatic Thematic Categorization of Documents Using a Fuzzy Taxonomy and Fuzzy Hierarchical Clustering

Abstract — In this paper we formally define the problem of automatic detection of thematic categories in a semantically indexed document, and identify the main obstacles to overcome in this process. Furthermore, we explain how detection of thematic categories can be achieved, with the use of a fuzzy quasi-taxonomic relation. Our approach relies on a fuzzy hierarchical clustering algorithm; this algorithm uses a similarity measure that is based on the notion of context. I

Context-Sensitive Semantic Query Expansion

Modern Information Retrieval Systems match the terms included in a user’s query with available documents, through the use of an index. A fuzzy thesaurus is used to enrich the query with associated terms. In this work, we use semantic entities, rather than terms; this allows us to use knowledge stored in a semantic encyclopedia, specifically the ordering relations, in order to perform a semantic expansion of the query. The process of query expansion takes into account the query context,which is defined as a fuzzy set of semantic entities. Furthermore, we integrate our approach with the user’s profile. 1