Relationships between two terms, keywords or names, constitute a significant part of our knowledge. Automatic extraction of such information allows the information to be stored in structured form so that it can be easily and accurately retrieved when needed. Such information can be used to build online search engines for highly specific and accurate information retrieval.
A novel approach has been developed to extract such information from raw text based on natural language processing (NLP) and graph theoretic algorithm. We applied the method on extracting protein-protein relationships in biomedical literature and obtained better performance than current methods. The method can be easily extended to extract other biological relationships between biological terms such as proteins, genes, pathways, diseases and drugs. The method can also be applied to other information domain to extract other relationships.
