Bob Wielinga

Semantic annotation and search of cultural-heritage collections: The MultimediaN E-Culture demonstrator

In this article we describe a Semantic Web application for semantic annotation and search in large virtual collections of cultural-heritage objects, indexed with multiple vocabularies. During the annotation phase we harvest, enrich and align collection metadata and vocabularies. The semantic-search facilities support keyword-based queries of the graph (currently 20M triples), resulting in semantically grouped result clusters, all representing potential semantic matches of the original query. We show two sample search scenarios. The annotation and search software is open source and is already being used by third parties. All software is based on established Web standards, in particular HTML/XML, CSS, RDF/OWL, SPARQL and JavaScript.

A method for converting thesauri to RDF/OWL

This paper describes a method for converting existing thesauri and related resources from their native format to RDF(S) and OWL. The method identifies four steps in the conversion process. In each step, decisions have to be taken with respect to the syntax or semantics of the resulting representation. Each step is supported through a number of guidelines. The method is illustrated through conversions of two large thesauri: MeSH and WordNet.

MultimediaN e-culture demonstrator

The main objective of the MultimediaN E-Culture project is to demonstrate how novel semantic-web and presentation technologies can be deployed to provide better indexing and search support within large virtual collections of cultural-heritage resources. The architecture is fully based on open web standards, in particular XML, SVG, RDF/OWL and SPARQL. One basic hypothesis underlying this work is that the use of explicit background knowledge in the form of ontologies/vocabularies/thesauri is in particular useful in information retrieval in knowledge-rich domains.

A redundancy-based method for the extraction of relation instances from the Web

The Semantic Web requires automatic ontology population methods. We developed an approach, that given existing ontologies, extracts instances of ontology relations, a specific subtask of ontology population. We use generic, domain-independent techniques to extract candidate relation instances from the Web and exploit the redundancy of information on the Web to compensate for loss of precision caused by the use of these generic methods. The candidate relation instances are then ranked based on co-occurrence with a small seed set. In an experiment, we extracted instances of the relation between artists and art styles. The results were manually evaluated against selected art resources. The method was also tested in the football domain. We also compare the performance of our ranking to that of a Google-hit count-based method.

Using triples for implementation: the triple20 ontology-manipulation tool

Triple20 is a ontology manipulation and visualization tool for languages built on top of the Semantic-Web RDF triple model. In this article we explain how a triple-centered design compares to the use of a separate proprietary internal data model. We show how to deal with the problems of such a low-level data model and show that it offers advantages when dealing with inconsistent or incomplete data as well as for integrating tools.

Extracting instances of relations from web documents using redundancy

In this document we describe our approach to a specific subtask of ontology population, the extraction of instances of relations. We present a generic approach with which we are able to extract information from documents on the web. The method exploits redundancy of information to compensate for loss of precision caused by the use of domain independent extraction methods. In this paper, we present the general approach and describe our implementation for a specific relation instance extraction task in the art domain. For this task, we describe experiments, discuss evaluation measures and present the results.

Relation instantiation for ontology population using the web

The Semantic Web requires automatic ontology population methods. We developed an approach, that given existing ontologies, extracts instances of ontology relations, a specific subtask of ontology population. We use generic, domain independent techniques to extract candidate relation instances from the Web and exploit the redundancy of information on the Web to compensate for loss of precision caused by the use of these generic methods. The candidate relation instances are then ranked based on co-occurrence with a seed set. In an experiment, we extracted instances of the relation between artists and art styles. The results were manually evaluated against selected art resources.