Keyword extraction, ranking, and organization for the neuroinformatics platform

Brain-related researches encompass many fields of studies and usually involve worldwide collaborations. Recognizing the value of these international collaborations for efficient use of resources and improving the quality of brain research, the International Neuroinformatics Coordinating Facility (INCF) started to coordinate the effort of establishing neuroinformatics (NI) centers and portal sites among the different participating countries. These NI centers and portal sites will serve as the conduit for the interchange of information and brain-related resources among different countries. In Japan, several NI platforms under the support of NIJC (NI Japan Center) are being developed with one platform called, Visiome, already operating and publicly accessible at “http://www.platform.visiome.org”. Each of these platforms requires their own set of keywords that represent important terms covering their respective fields of study. One important function of this predefined keyword list is to help contributors classify the contents of their contributions and group related resources. It is vital, therefore, that this predefined list should be properly chosen to cover the necessary areas. Currently, the process of identifying these appropriate keywords relies on the availability of human experts which does not scale well considering that different areas are rapidly evolving. This problem prompted us to develop a tool to automatically filter the most likely terms preferred by human experts. We tested the effectiveness of the proposed approach using the abstracts of the Vision Research Journal (VR) and Investigative Ophthalmology and Visual Science Journal (IOVS) as source files.