Background. Recent advances in computational and biological methods in last two decades have remarkably changed the scale\r\nof biomedical research and with it began the unprecedented growth in both the production of biomedical data and amount of\r\npublished literature discussing it. An automated extraction system coupled with a cognitive search and navigation service over\r\nthese document collections would not only save time and effort, but also pave the way to discover hitherto unknown information\r\nimplicitly conveyed in the texts. Results. We developed a novel framework (named ââ?¬Å?BioEveââ?¬Â) that seamlessly integrates Faceted\r\nSearch (Information Retrieval) with Information Extraction module to provide an interactive search experience for the researchers\r\nin life sciences. It enables guided step-by-step search query refinement, by suggesting concepts and entities (like genes, drugs, and\r\ndiseases) to quickly filter and modify search direction, and thereby facilitating an enriched paradigm where user can discover\r\nrelated concepts and keywords to search while information seeking. Conclusions. The BioEve Search framework makes it easier\r\nto enable scalable interactive search over large collection of textual articles and to discover knowledge hidden in thousands of\r\nbiomedical literature articles with ease.
Loading....