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.
This work is partly supported by the ontology grant NIH/NINDS R01NS058296 and NIH/Neuroscience Blueprint contract HHSN271200800035C for the Neuroscience Information Framework (NIF).
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Ozyurt, I.B., Condit, C., Gupta, A. (2012). Processing Semantic Keyword Queries for Scientific Literature. In: Bouma, G., Ittoo, A., Métais, E., Wortmann, H. (eds) Natural Language Processing and Information Systems. NLDB 2012. Lecture Notes in Computer Science, vol 7337. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31178-9_51
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DOI: https://doi.org/10.1007/978-3-642-31178-9_51
Publisher Name: Springer, Berlin, Heidelberg
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