Robustness beyond shallowness: incremental deep parsing
Natural Language Engineering
Boilerplate detection using shallow text features
Proceedings of the third ACM international conference on Web search and data mining
Labelling and spatio-temporal grounding of news events
WSA '10 Proceedings of the NAACL HLT 2010 Workshop on Computational Linguistics in a World of Social Media
Large-scale hierarchical text classification without labelled data
Proceedings of the fourth ACM international conference on Web search and data mining
A realistic architecture for the semantic web
RuleML'05 Proceedings of the First international conference on Rules and Rule Markup Languages for the Semantic Web
Improving the real-time performance of heterogeneous extremely large datasets
Proceedings of the 17th Panhellenic Conference on Informatics
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In this paper we present and discuss the implementation and deployment of the Protocol for Web Description Resources (POWDER) W3C Recommendation for a large RDF repository containing millions of triples. POWDER enables taking advantage of natural groupings of URIs and their reflection on the denoted things' properties; our application implements a POWDER service that intercepts the API between the RDF store and the inference layer above it and provides annotations that appear as explicit statements to the inference service. The approach is tested on a multi million-triple store of news documents and events, where it achieves dramatic savings on storage space without impacting querying time.