LitLinker: capturing connections across the biomedical literature

The explosive growth in the biomedical literature has made it difficult for researchers to keep up with advancements, even in their own narrow specializations. In addition, this current volume of information has created barriers that prevent researchers from exploring connections to their own work from other parts of the literature. Although potentially useful connections might permeate the literature, they will remain buried without new kinds of tools to help researchers capture new knowledge that bridges gaps across distinct sections of the literature. In this paper, we present LitLinker, a system that incorporates knowledge-based methodologies, natural-language processing techniques, and a data-mining algorithm to mine the biomedical literature for new, potential causal links between biomedical terms. Our results from a well-known textmining example show that LitLinker can capture these novel, interesting connections in an open-ended fashion, with less manual intervention than in p...

• Type: Conference
• Year: 2003
• Where: KCAP
• Authors: Wanda Pratt, Meliha Yetisgen-Yildiz
• Keywords: Biomedical Literature, KCAP 2003, Natural-language Processing Techniques, Well-known Textmining Example