Sesame: A Generic Architecture for Storing and Querying RDF and RDF Schema
ISWC '02 Proceedings of the First International Semantic Web Conference on The Semantic Web
Natural Language Engineering
Data Integration using Semantic Technology: A use case
RULEML '06 Proceedings of the Second International Conference on Rules and Rule Markup Languages for the Semantic Web
Explorations in the use of semantic web technologies for product information management
Proceedings of the 16th international conference on World Wide Web
The YAGO-NAGA approach to knowledge discovery
ACM SIGMOD Record
Web Semantics: Science, Services and Agents on the World Wide Web
Lifecycle-support in architectures for ontology-based information systems
ISWC'07/ASWC'07 Proceedings of the 6th international The semantic web and 2nd Asian conference on Asian semantic web conference
Aletheia--Improving Industrial Service Lifecycle Management by Semantic Data Federations
AINA '10 Proceedings of the 2010 24th IEEE International Conference on Advanced Information Networking and Applications
Integrating explicit semantic analysis for ontology-based resource selection
Proceedings of the 13th International Conference on Information Integration and Web-based Applications and Services
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Product-related information can be found in various data sources and formats across the product lifecycle. Effectively exploiting this information requires the federation of these sources, the extraction of implicit information, and the efficient access to this comprehensive knowledge base. Existing solutions for product information management (PIM) are usually restricted to structured information, but most of the business-critical information resides in unstructured documents. We present a generic architecture for federating heterogeneous information from various sources, and argue how this process benefits from using semantic representations. An reference implementation tailor-made to business users is explained and evaluated. We also discuss several issues we experienced that we believe to be valuable for researchers and implementers of semantic information systems, as well as the information retrieval community.