Slicing through the Scientific Literature

Authors:
Christopher J. Baker;Patrick Lambrix;Jonas Laurila Bergman;Rajaraman Kanagasabai;Wee Tiong Ang
Affiliations:
Department of Computer Science & Applied Statistics, University of New Brunswick, Canada;Department of Computer and Information Science, Linköpings universitet, Sweden;Department of Computer and Information Science, Linköpings universitet, Sweden;Data Mining Department, Institute for Infocomm Research, Agency for Science Technology and Research, Singapore;Data Mining Department, Institute for Infocomm Research, Agency for Science Technology and Research, Singapore
Venue:
DILS '09 Proceedings of the 6th International Workshop on Data Integration in the Life Sciences
Year:
2009

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Abstract

Success in the life sciences depends on access to information in knowlegde bases and literature. Finding and extracting the relevant information depends on a user's domain knowledge and the knowledge of the search technology. In this paper we present a system that helps users formulate queries and search the scientific literature. The system coordinates ontologies, knowledge representation, text mining and NLP techniques to generate relevant queries in response to keyword input from the user. Queries are presented in natural language, translated to formal query syntax and issued to a knowledge base of scientific literature, documents or aligned document segments. We describe the components of the system and exemplify using real-world examples.