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We propose an inexpensive and scalable approach for curation that takes advantage of automatic information extraction methods as a starting point, and is based on the premise that if there are a lot of articles, then there must be a lot of readers and authors of these articles. Thus we provide a mechanism by which the readers of the articles can participate and collaborate in the curation of information.

Collaborative Curation of Data from Bio-medical Texts and Abstracts and Its integration