Design patterns: elements of reusable object-oriented software
Design patterns: elements of reusable object-oriented software
User-Driven Ontology Evolution Management
EKAW '02 Proceedings of the 13th International Conference on Knowledge Engineering and Knowledge Management. Ontologies and the Semantic Web
Pellet: A practical OWL-DL reasoner
Web Semantics: Science, Services and Agents on the World Wide Web
Ontology-driven, unsupervised instance population
Web Semantics: Science, Services and Agents on the World Wide Web
Semantic annotation, indexing, and retrieval
Web Semantics: Science, Services and Agents on the World Wide Web
Query Answering for OWL-DL with rules
Web Semantics: Science, Services and Agents on the World Wide Web
Entity Resolution and Information Quality
Entity Resolution and Information Quality
An ontology-driven framework towards building enterprise semantic information layer
Advanced Engineering Informatics
An Approach for Populating and Enriching Ontology-Based Repositories
DEXA '13 Proceedings of the 2013 24th International Workshop on Database and Expert Systems Applications
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Publically available text-based documents (e.g. news, meeting transcripts) are a very important source of knowledge for organizations and individuals. These documents refer domain entities such as persons, places, professional positions, decisions, actions, etc. Querying these documents (instead of browsing, searching and finding) is a very relevant task for any person in general, and particularly for professionals dealing with intensive knowledge tasks. Querying text-based documents' data, however, is not supported by common technology. For that, such documents' content has to be explicitly and formally captured into knowledge base facts. Making use of automatic NLP processes for capturing such facts is a common approach, but their relatively low precision and recall give rise to data quality problems. Further, facts existing in the documents are often insufficient to answer complex queries and, therefore, it is often necessary to enrich the captured facts with facts from third-party repositories (e.g. public LOD, private IS databases). This paper describes the adopted process to identify what data is currently missing from the knowledge base repository and which is desirable to collect from external repositories. The proposed process aims to foster and is driven by OWL DL inference-based instance (ABox) classification, which is supported by the constraints of the TBox.