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BioTextRetriever : yet another Information Retrieval system

It is of capital importance for every researcher to be aware of the work that has been done in his research area. However, finding “interesting/relevant” publications in the overwhelming amount of documents available in the Internet is quite difficult. We propose the use of Text Mining to address this information overload problem by automating the process of extracting relevant papers from very large repositories of scientific literature. We present in this paper, the automatic construction of a classifier capable of selecting the relevant papers among the whole MEDLINE, that is part of a software developed tool: BioTextRetriever. The empirical evaluation of the work shows a classifier’s accuracies around 95%.