An up-to-date knowledge-based literature search and exploration framework for focused bioscience domains

  • Authors:

  • Ramakanth Kavuluru;Christopher Thomas;Amit P. Sheth;Victor Chan;Wenbo Wang;Alan Smith;Armando Soto;Amy Walters

  • Affiliations:

  • Wright State University, Dayton, OH, USA;Wright State University, Dayton, OH, USA;Wright State University, Dayton, OH, USA;Air Force Research Lab, Dayton, OH, USA;Wright State University, Dayton, OH, USA;Wright State University, Dayton, OH, USA;Air Force Research Lab, Dayton, OH, USA;Air Force Research Lab, Dayton, OH, USA

  • Venue:
  • Proceedings of the 2nd ACM SIGHIT International Health Informatics Symposium
  • Year:
  • 2012

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Abstract

In domain-specific search systems, knowledge of a domain of interest is embedded as a backbone that guides the search process. But the knowledge used in most such systems 1. exists only for few well known broad domains; 2. is of a basic nature: either purely hierarchical or involves only few relationship types; and 3. is not always kept up-to-date missing insights from recently published results. In this paper we present a framework and implementation of a focused and up-to-date knowledge-based search system, called Scooner, that utilizes domain-specific knowledge extracted from recent bioscience abstracts. To our knowledge, this is the first attempt in the field to address all three shortcomings mentioned above. Since recent introduction for operational use at Applied Biotechnology Branch of AFRL, some biologists are using Scooner on a regular basis, while it is being made available for use by many more. Initial evaluations point to the promise of the approach in addressing the challenge we set out to address.