Semantic Method of Recovering of Medical Articles

The amount of information produced today reached an unprecedented contingent in history, which makes it difficult to locate relevant documents in a search. This situation leads to the need to use tools that facilitate the search, making information retrieval area increasingly important in the development of this context. Based on the organization of documents and ontology, information retrieval area has the challenge of getting smarter ways to recovery than just select syntactically documents, exploiting to the full the semantic context when selecting the information. This paper presents a semantic enrichment method that seeks to improve the quality of results when querying a database of medical articles. The proposed method performs a search on the repository of articles that is submitted to latent semantic analysis together with the National Cancer Institute (NCI) ontology and the lexical WordNet ontology database. After this joint treatment, the semantic relationship of those new terms to the survey conducted in the context is performed in order to improve the accuracy of recovery and enabling the retrieve of more relevant articles regarding the search.