skip to main content
10.1145/3183713.3193551acmconferencesArticle/Chapter ViewAbstractPublication PagesmodConference Proceedingsconference-collections
research-article

An Ontology based Dialog Interface to Database

Published: 27 May 2018 Publication History

Abstract

In this paper, we extend the state-of-the-art NLIDB system and present a dialog interface to relational databases. Dialog interface enables users to automatically exploit the semantic context of the conversation while asking natural language queries over RDBMS, thereby making it simpler to express complex questions in a natural, piece-wise manner. We propose novel ontology-driven techniques for addressing each of the dialog-specific challenges such as co-reference resolution, ellipsis resolution, and query disambiguation, and use them in determining the overall intent of the user query. We demonstrate the applicability and usefulness of dialog interface over two different domains viz. finance and healthcare.

References

[1]
Raquel Fernández, Jonathan Ginzburg, and Shalom Lappin. 2007. Classifying non-sentential utterances in dialogue: A machine learning approach. Computational Linguistics Vol. 33, 3 (2007), 397--427.
[2]
Matthew Henderson, Blaise Thomson, and Jason D Williams. 2014. The third dialog state tracking challenge. In Spoken Language Technology Workshop (SLT), 2014 IEEE. IEEE, 324--329.
[3]
Fei Li and HV Jagadish. 2014. Constructing an interactive natural language interface for relational databases. Proceedings of the VLDB Endowment Vol. 8, 1 (2014), 73--84.
[4]
Christopher D Manning, Mihai Surdeanu, John Bauer, Jenny Rose Finkel, Steven Bethard, and David McClosky. 2014. The stanford corenlp natural language processing toolkit. ACL (System Demonstrations). 55--60.
[5]
Vincent Ng. 2010. Supervised noun phrase coreference research: The first fifteen years Proceedings of the 48th annual meeting of the association for computational linguistics. Association for Computational Linguistics, 1396--1411.
[6]
Dinesh Raghu, Sathish Indurthi, Jitendra Ajmera, and Sachindra Joshi. 2015. A Statistical Approach for Non-Sentential Utterance Resolution for Interactive QA System 16th Annual Meeting of the Special Interest Group on Discourse and Dialogue, Vol. Vol. 335.
[7]
Diptikalyan Saha, Avrilia Floratou, Karthik Sankaranarayanan, Umar Farooq Minhas, Ashish R. Mittal, and Fatma Özcan. 2016. ATHENA: An Ontology-driven System for Natural Language Querying over Relational Data Stores. Proc. VLDB Endow. Vol. 9, 12 (Aug. 2016), 1209--1220.

Cited By

View all
  • (2021)Bootstrapping Chatbot Interfaces to DatabasesProceedings of the 3rd ACM India Joint International Conference on Data Science & Management of Data (8th ACM IKDD CODS & 26th COMAD)10.1145/3430984.3431011(47-55)Online publication date: 2-Jan-2021
  • (2018)Information Processing and Retrieval from CSV File by Natural Language2018 IEEE 3rd International Conference on Communication and Information Systems (ICCIS)10.1109/ICOMIS.2018.8644947(212-216)Online publication date: Dec-2018

Recommendations

Comments

Information & Contributors

Information

Published In

cover image ACM Conferences
SIGMOD '18: Proceedings of the 2018 International Conference on Management of Data
May 2018
1874 pages
ISBN:9781450347037
DOI:10.1145/3183713
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

Sponsors

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 27 May 2018

Permissions

Request permissions for this article.

Check for updates

Author Tags

  1. database
  2. dialog
  3. natural language interface
  4. ontology

Qualifiers

  • Research-article

Funding Sources

  • Ashish Rakeshkumar Mittal

Conference

SIGMOD/PODS '18
Sponsor:

Acceptance Rates

SIGMOD '18 Paper Acceptance Rate 90 of 461 submissions, 20%;
Overall Acceptance Rate 785 of 4,003 submissions, 20%

Contributors

Other Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

  • Downloads (Last 12 months)11
  • Downloads (Last 6 weeks)0
Reflects downloads up to 03 Mar 2025

Other Metrics

Citations

Cited By

View all
  • (2021)Bootstrapping Chatbot Interfaces to DatabasesProceedings of the 3rd ACM India Joint International Conference on Data Science & Management of Data (8th ACM IKDD CODS & 26th COMAD)10.1145/3430984.3431011(47-55)Online publication date: 2-Jan-2021
  • (2018)Information Processing and Retrieval from CSV File by Natural Language2018 IEEE 3rd International Conference on Communication and Information Systems (ICCIS)10.1109/ICOMIS.2018.8644947(212-216)Online publication date: Dec-2018

View Options

Login options

View options

PDF

View or Download as a PDF file.

PDF

eReader

View online with eReader.

eReader

Figures

Tables

Media

Share

Share

Share this Publication link

Share on social media