Evaluating WordNet-based Measures of Lexical Semantic Relatedness
Computational Linguistics
Automatic Ontology Identification for Reuse
WI '07 Proceedings of the IEEE/WIC/ACM International Conference on Web Intelligence
WordNet: similarity - measuring the relatedness of concepts
AAAI'04 Proceedings of the 19th national conference on Artifical intelligence
Using information content to evaluate semantic similarity in a taxonomy
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 1
Automated ontology generation using spatial reasoning
KSEM'10 Proceedings of the 4th international conference on Knowledge science, engineering and management
| Hi-index | 0.00 |
Users organize personal information in various ways. We believe that this process could be expedited and improved by using domain ontologies. The main problem with this idea is the lack of automatic tools that help non-expert users to build and maintain their own ontologies. In this study we report progress in the process of adapting ontologies to better represent a given set of documents centered on a topic of interest. More specifically we investigate automatic approaches to enhance the representation of the concepts within the domain ontology. We show that our approach can enrich the vocabulary of each concept with words mined from the set of small documents provided. The method we propose is based on efficient text mining approaches combined with semantic information from WordNet.