The structure-mapping engine: algorithm and examples
Artificial Intelligence
Probabilistic Datalog—a logic for powerful retrieval methods
SIGIR '95 Proceedings of the 18th annual international ACM SIGIR conference on Research and development in information retrieval
Similarity Flooding: A Versatile Graph Matching Algorithm and Its Application to Schema Matching
ICDE '02 Proceedings of the 18th International Conference on Data Engineering
TMRAP – topic maps remote access protocol
TMRA'05 Proceedings of the First international conference on Charting the Topic Maps Research and Applications Landscape
Real-Time generation of topic maps from speech streams
TMRA'05 Proceedings of the First international conference on Charting the Topic Maps Research and Applications Landscape
tolog – a topic maps query language
TMRA'05 Proceedings of the First international conference on Charting the Topic Maps Research and Applications Landscape
TM/XML – topic maps fragments in XML
TMRA'05 Proceedings of the First international conference on Charting the Topic Maps Research and Applications Landscape
Indices, meaning and topic maps: some observations
TMRA'06 Proceedings of the 2nd international conference on Topic maps research and applications
Real-Time generation of topic maps from speech streams
TMRA'05 Proceedings of the First international conference on Charting the Topic Maps Research and Applications Landscape
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Topic Maps are the international industry standard for semantic information integration. Appropriate means for Topic Map exchange are crucial for its success as integration technology. Topic Map exchange bases on the governing Subject Equality decision approach, the decision whether two Subject Proxies indicate identical Subjects. This paper discusses the ‘absence of shared vocabularies' in the context of these decisions. Thereby, a differentiation between Referential and Structuralist Subject Equality decision approaches is introduced. All existing approaches to Topic Map exchange base on the TMDM. This implies a Referential Subject Equality decision approach and bound to a concrete Subject Map Disclosure (SMD) ontology and Subject Map (SM) vocabulary. This paper introduces a Structuralist Subject Equality decision approach which is called SIM. It allows the exchange of Topic Maps in the absence of a shared SM ontology and SM vocabulary.