A Science Model Driven Retrieval Prototype

This paper is about a better understanding on the structure and dynamics of science and the usage of these insights for compensating the typical problems that arises in metadata-driven Digital Libraries. Three science model driven retrieval services are presented: co-word analysis based query expansion, re-ranking via Bradfordizing and author centrality. The services are evaluated with relevance assessments from which two important implications emerge: (1) precision values of the retrieval service are the same or better than the tfidf retrieval baseline and (2) each service retrieved a disjoint set of documents. The different services each favor quite other – but still relevant – documents than pure term-frequency based rankings. The proposed models and derived retrieval services therefore open up new viewpoints on the scientific knowledge space and provide an alternative framework to structure scholarly information systems.

• Type: Journal
• Year: 2011
• Where: CORR
• Authors: Philipp Mayr, Philipp Schaer, Peter Mutschke
• Keywords: CORR 2011, Education, Metadata-driven Digital Libraries, Retrieval Services, Tfidf Retrieval Baseline