Please use this identifier to cite or link to this item: http://bura.brunel.ac.uk/handle/2438/19203
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dc.contributor.authorSkeggs, R-
dc.contributor.authorLauria, S-
dc.date.accessioned2019-10-01T10:22:00Z-
dc.date.available2019-09-29-
dc.date.available2019-10-01T10:22:00Z-
dc.date.issued2019-09-29-
dc.identifier.citationJournal of Software Engineering and Applications, 2019, 12 (9), pp. 365 - 382 (18)en_US
dc.identifier.issn1945-3116-
dc.identifier.urihttps://bura.brunel.ac.uk/handle/2438/19203-
dc.description.abstractCopyright © 2019 by author(s) and Scientific Research Publishing Inc. The performance and reliability of converting natural language into structured query language can be problematic in handling nuances that are prevalent in natural language. Relational databases are not designed to understand language nuance, therefore the question why we must handle nuance has to be asked. This paper is looking at an alternative solution for the conversion of a Natural Language Query into a Structured Query Language (SQL) capable of being used to search a relational database. The process uses the natural language concept, Part of Speech to identify words that can be used to identify database tables and table columns. The use of Open NLP based grammar files, as well as additional configuration files, assist in the translation from natural language to query language. Having identified which tables and which columns contain the pertinent data the next step is to create the SQL statement.en_US
dc.format.extent365 - 382 (18)-
dc.language.isoenen_US
dc.publisherScientific Research Publishing Inc.en_US
dc.subjectNLIDBen_US
dc.subjectnatural language processingen_US
dc.subjectdatabase queryen_US
dc.subjectdata miningen_US
dc.titleA Shallow Parsing Approach to Natural Language Queries of a Databaseen_US
dc.typeArticleen_US
dc.identifier.doihttps://doi.org/10.4236/jsea.2019.129022-
dc.relation.isPartOfJournal of Software Engineering and Applications-
pubs.issue9-
pubs.publication-statusPublished-
pubs.volume12-
Appears in Collections:Dept of Computer Science Research Papers

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