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Processing Semantic Keyword Queries for Scientific Literature

  • Ibrahim Burak Ozyurt
  • Christopher Condit
  • Amarnath Gupta
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7337)

Abstract

In this short paper, we present early results from an ongoing research on creating a new graph-based representation from NLP analysis of scientific documents so that the graph can be utilized for answering structured queries on NL-processed data. We present a sketch of the data model and the query language to show how scientifically meaningful queries can be posed against this graph structure.

Keywords

Query Language Semantic Model Parse Tree Keyword Query Amyloidogenic Protein 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Ibrahim Burak Ozyurt
    • 1
  • Christopher Condit
    • 2
  • Amarnath Gupta
    • 2
  1. 1.Department of PsychiatryUniversity of CaliforniaSan Diego, La JollaUSA
  2. 2.San Diego Supercomputer CenterUniversity of CaliforniaSan Diego, La JollaUSA

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