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Cited by 534

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Developing a natural language interface to complex data

Hendrix, Gary G., Sacerdoti, Earl D., Sagalowicz, Daniel, Slocum, Jonathan·1978·ACM Transactions on Database Systems

Abstract

Aspects of an intelligent interface that provides natural language access to a large body of data distributed over a computer network are described. The overall system architecture is presented, showing how a user is buffered from the actual database management systems (DBMSs) by three layers of insulating components. These layers operate in series to convert natural language queries into calls to DBMSs at remote sites. Attention is then focused on the first of the insulating components, the natural language system. A pragmatic approach to language access that has proved useful for building interfaces to databases is described and illustrated by examples. Special language features that increase system usability, such as spelling correction, processing of incomplete inputs, and run-time system personalization, are also discussed. The language system is contrasted with other work in applied natural language processing, and the system's limitations are analyzed.

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Metadata

Authors
Hendrix, G. G., Sacerdoti, E. D., Sagalowicz, D., & Slocum, J.
Venue
ACM Transactions on Database Systems
Published
1978-06
Volume
3
Issue
2
Pages
105-147
ISSN
  • 0362-5915 (ISSN-L)
  • 1557-4644
OpenAlex
W2043794661
Cited by
534
References
0
FWCI
43.12
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Developing a natural language interface to complex data. https://app.cochat.ai/papers/10.1145/320251.320253
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Hendrix, G. G., Sacerdoti, E. D., Sagalowicz, D., & Slocum, J. (1978). Developing a natural language interface to complex data. ACM Transactions on Database Systems. https://doi.org/10.1145/320251.320253

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.