Briefs

2/4/2005 5:00:00 PM - With 40,000 science articles published a month, the challenge is finding the information that matters the most. Researchers discuss the classic Boolean model and where open source tools will take us next.

by Sarah Lysecki, ITbusiness.ca

Researchers are turning to text mining tools as one way to more efficiently and accurately extract information from large volumes of scientific data.

With the proliferation of scientific data being produced on a daily basis, researchers are often faced with the challenge of sifting through large databases to locate information that could lead to new medical treatment options.

That was the main topic of discussion at a workshop organized by the Ontario Centre for Genomic Computing (OCGC) on Friday, which brought together bioinformaticists and text-mining experts from Ontario and abroad.

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�The geneticists are overwhelmed with the number of papers they have to read,� said Martin. �It�s easy to miss something.�

To address this problem, NRC-IIT in conjunction with the NRC Institute for Biological Sciences (NRC-IBS) and the Samuel Lunenfeld Institute and Blueprint International is developing a collection of text and language-based processing tools. Currently in its first phase, the LitMiner project, which Martin calls �content management for biology,� aims to integrate several existing text mining tools into one package. The project started two years ago.

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