R.F. Murphy, Z. Kou, J. Hua, M. Joffe, and W.W. Cohen (USA)
Knowledge and Information Retrieval, Multimedia Databases, Data and Text Mining, Location Proteomics
Previous applications of information extraction methods to articles in biomedical journals have predominantly been based on interpreting article text. This often leads to uncertainty about whether statements that are found are attempts at reviews or summaries of data in other papers, conjectures or opinions, or conclusions from evidence presented in the paper at hand. The ability to extract information from the primary data presented in an article, which is often in the form of images, would allow more accurate information to be extracted. Towards this end, we have built a system that extracts information on one particular aspect of biology from a combination of text and image in journal articles. The design and performance of this system are described here, along with conclusions about possible improvements in the scientific publishing process that we have drawn from our implementation process.
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