1. Managing Semantic Content for the Web
Amit Sheth, Clemens Bertram, David Avant, Brian Hammond, Krysztof Kochut, and Yashodhan Warke (2002)
Voquette and the University of Georgia

2. Developed by the University of Georgia and Venquette
SCORE
SCORE := Semantic Content Organization and Retrieval Engine
Four key capabilities:
Semantic organization and use of metadata
Classification with a combination of different methods, e.g. proabilistic (Bayesian), learning (Hidden Markov Models) and knowledge-based
Semantic normalization
Same metadata for same content
Semantic search
Semantic association
Concept linking (e.g. with rdfs:sameAs)
Developed by the University of Georgia and Venquette

3. SCORE – Components
Metadata extraction and classification (both stored in content metabase)
Entity extraction (stored in knowledge base)
API for semantic application

4. SCORE – Architecture Diagram1 2 3

5. First approach of a semantic content organization and retrieval engine
Summary
First approach of a semantic content organization and retrieval engine
Voquette website offline -> Project not active maintained
Not able to find the software for further analysis
Architecture could be simplified with current technologies (e.g. the use of a triplestore)