Text Mining & Natural Language Processing

Over the last decade, the GIB has been involved in a large number of text mining and information extraction/retrieval projects. We have been active in accessing and extracting knowledge from various unstructured sources, and from the biomedical literature available in PubMed. Bringing together structured and text-based sources is an exciting challenge for biomedical informaticians, since the most relevant biomedical sources belong to one of these categories. Unfortunately, the methods and tools provided by state-of-the-art database integration tools cannot be reused to bridge together structured and non-structured (text-based) sources, since all of them require the individual sources to be equipped with a logical schema. To address this issue, we created various approaches based on text mining techniques to automatically create a logical schema for non-structured sources. As seen in other sections, we have widely used text mining techniques in a large number of areas.