We found a match
Your institution may have rights to this item. Sign in to continue.
- Title
A multi-phase correlation search framework for mining non-taxonomic relations from unstructured text.
- Authors
Wong, Mei; Abidi, Syed; Jonsen, Ian
- Abstract
Over the last decade, ontology engineering has been pursued by 'learning' the ontology from domain-specific electronic documents. Most of the research works are focused on extraction of concepts and taxonomic relations. The extraction of non-taxonomic relations is often neglected and not well researched. In this paper, we present a multi-phase correlation search framework to extract non-taxonomic relations from unstructured text. Our framework addresses the two main problems in any non-taxonomic relations extraction: (a) the discovery of non-taxonomic relations and (b) the labelling of non-taxonomic relations. First, our framework is capable of extracting correlated concepts beyond ordinary search window size of a single sentence. Interesting correlations are then filtered using association rule mining with lift interestingness measure. Next, our framework distinguishes non-taxonomic concept pairs from taxonomic concept pairs based on existing domain ontology. Finally, our framework features the usage of domain related verbs as labels for the non-taxonomic relations. Our proposed framework has been tested with the marine biology domain. Results have been validated by domain experts showing reliable results as well as demonstrate significant improvement over traditional association rule approach in search of non-taxonomic relations from unstructured text.
- Subjects
STATISTICAL correlation; ELECTRONIC records; ASSOCIATION rule mining; MARINE biology; ONTOLOGIES (Information retrieval)
- Publication
Knowledge & Information Systems, 2014, Vol 38, Issue 3, p641
- ISSN
0219-1377
- Publication type
Article
- DOI
10.1007/s10115-012-0593-7