Intelligent Information Access from Scientific Papers

We describe a novel search engine for scientific literature. The system allows for sentence-level search starting from portable document format (PDF) files, and integrates text and image search, thus facilitating the retrieval of information present in tables and figures. It allows the user to generate in an intuitive manner complex queries for search terms that are related through particular grammatical (and thus implicitly semantic) relations. The system uses grid processing to parallelise the analysis of large numbers of scientific papers. It is currently undergoing user evaluation, but we report some preliminary evaluation and comparison with Google Scholar, demonstrating its utility. Finally, we discuss future work and the potential and complimentarity of the system for patent search.