Optimized dynamic semantic composition of services
Proceedings of the 2008 ACM symposium on Applied computing
News Annotations for Navigation by Semantic Similarity
KI '08 Proceedings of the 31st annual German conference on Advances in Artificial Intelligence
Ontology-based relevance analysis for automatic reference tracking
International Journal of Computer Applications in Technology
Ontology - supported machine learning and decision support in biomedicine
DILS'07 Proceedings of the 4th international conference on Data integration in the life sciences
Research on a novel word co-occurrence model and its application
KSEM'07 Proceedings of the 2nd international conference on Knowledge science, engineering and management
Agregação inteligente de RSS utilizando uma taxonomia construída colaborativamente
Companion Proceedings of the XIV Brazilian Symposium on Multimedia and the Web
Comparative evaluation of ontology-based Automatic Reference Tracking (ART)
International Journal of Networking and Virtual Organisations
Clustering of rough set related documents with use of knowledge from DBpedia
RSKT'11 Proceedings of the 6th international conference on Rough sets and knowledge technology
A semantic matching of information segments for tolerating error chinese words
WISE'06 Proceedings of the 7th international conference on Web Information Systems
Ontology-Based similarity between text documents on manifold
ASWC'06 Proceedings of the First Asian conference on The Semantic Web
Discovery and composition of services for context-aware systems
EuroSSC'06 Proceedings of the First European conference on Smart Sensing and Context
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In this work we consider ontologies as knowledgestructures that specify terms, their properties and relationsamong them to enable knowledge extraction fromtexts. We represent ontologies using a graph-basedmodel that reflect semantic relationship between conceptsand apply them to text analysis and comparison.Instead of raw document comparison we compare documentfootprint enhanced with concepts from the ontology(using different enhancement algorithms). Theresult of this process may be that documents not similarprior to the enhancement become similar (semanticallyon some abstraction level) after the enhancement.This is because the enhancement process may introducein the document footprint abstract concepts from theontology. Using the ontology we can enhance the foot-printsby adding concepts that are not present in theoriginal document. We may use synonyms for a horizontalexpansion and broader terms/superclasses/typesin a vertical expansion or both for that matter.