Search

In cultural heritage, large virtual collections are coming into existence. Such collections contain heterogeneous sets of metadata and vocabulary concepts, originating from multiple sources. In the context of the E-Culture demonstrator we have shown earlier that such virtual collections can be effectively explored with keyword search and semantic clustering. In this paper we describe the design rationale of ClioPatria, an open-source system which provides APIs for scalable semantic graph search. The use of ClioPatria’s search strategies is illustrated with a realistic use case: searching for "Picasso". We discuss details of scalable graph search, the required OWL reasoning functionalities and show why SPARQL queries are insufficient for solving the search problem.

In this paper we present i) an approach for clustering authors according to their citation distributions and ii) an ontology, the Bibliometric Data Ontology, for supporting the formal representation of such clusters. This method allows the formulation of queries which take in consideration the citation behaviour of an author and predicts with a good level of accuracy future citation behaviours. We evaluate our approach with respect to alternative solutions and discuss the predicting abilities of the identified clusters.