Semantic Integration of Information Through Relation Mining - Application to Bio-medical Text Processing
Semantic frameworks can be used to improve the accuracy and expressiveness of natural language processing for the purpose of extracting meaning from text documents. Such a framework represents knowledge using semantic networks and can be generated using information mined from text documents. The key issue however is to identify relevant concepts and their inter-relationships. In this paper, we have presented a scheme for semantic integration of information extracted from text documents. The extraction principle is based on linguistic and semantic analysis of text. Entities and relations are extracted using Natural Language Processing techniques. A method for collating information extracted from multiple sources to generate the semantic net is also presented. The efficacy of the proposed semantic framework is established through experiments carried out for visualizing information embedded in biomedical texts extracted from PubMed database.
KeywordsRelation extraction Semantic net Knowledge visualization NLP
- 1.Castro, A.G., Rocca-Serra1, P., Stevens, R., Taylor1, C., Nashar, K., Ragan, M.A., Sansone, S.-A.: The use of concept maps during knowledge elicitation in ontology development processes - the nutrigenomics use case, BMC Bioinformatics (May 25, 2006)Google Scholar
- 2.Ciaramita, M., Gangemi, A., Ratsch, E., Saric, J., Rojas, I.: Unsupervised Learning of Semantic Relations between Concepts of a Molecular Biology On-tology. In: Proceedings of the 19th International Joint Conference on Artificial Intelligence (IJCAI 2005), pp. 659–664 (2005)Google Scholar
- 3.Cox, E.: A Hybrid Technology Approach to Free-Form Text Data Mining, http://scianta.com/pubs/AR-PA-007.htm
- 5.García, R., Celma, O.: Semantic Integration and Retrieval of Multimedia Metadata. In: Knowledge Mark-up and Semantic Annotation Workshop, Semannot 2005. CEUR (2005)Google Scholar
- 6.Wagner, C., Cheung, K.S.K., Rachael, K.F.: Building Semantic Webs for e-government with Wiki technology. Electronic Government 3(1) (2006)Google Scholar