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The use of theorem-proving techniques in question-answering systems

Authors:

C. Cordell Green,

Bertram RaphaelAuthors Info & Claims

ACM '68: Proceedings of the 1968 23rd ACM national conference

Pages 169 - 181

https://doi.org/10.1145/800186.810578

Published: 01 January 1968 Publication History

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Abstract

For the purpose of this paper, a question-answering system is a computer program that has at least the following three characteristics:

(1) The ability to accept statements of fact and store them in its memory

(2) The ability to search stored information efficiently and to recognize items that are relevant to a particular query

(3) The ability to respond appropriately to a question by identifying and presenting the answer if it is present in memory, and by deducing a reasonable logical response from relevant knowledge if the complete answer is not explictly available.

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Cited By

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Sequeda JAllemang DJacob B(2024)A Benchmark to Understand the Role of Knowledge Graphs on Large Language Model's Accuracy for Question Answering on Enterprise SQL DatabasesProceedings of the 7th Joint Workshop on Graph Data Management Experiences & Systems (GRADES) and Network Data Analytics (NDA)10.1145/3661304.3661901(1-12)Online publication date: 14-Jun-2024
https://dl.acm.org/doi/10.1145/3661304.3661901
Ciatto GSabbatini FAgiollo AMagnini MOmicini A(2024)Symbolic Knowledge Extraction and Injection with Sub-symbolic Predictors: A Systematic Literature ReviewACM Computing Surveys10.1145/364510356:6(1-35)Online publication date: 8-Feb-2024
https://dl.acm.org/doi/10.1145/3645103
Allemang DSequeda J(2024)Increasing the Accuracy of LLM Question-Answering Systems with OntologiesThe Semantic Web – ISWC 202410.1007/978-3-031-77847-6_18(324-339)Online publication date: 27-Nov-2024
https://doi.org/10.1007/978-3-031-77847-6_18
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Index Terms

The use of theorem-proving techniques in question-answering systems
1. Computing methodologies
  1. Artificial intelligence
    1. Knowledge representation and reasoning
  2. Symbolic and algebraic manipulation
    1. Symbolic and algebraic algorithms
      1. Theorem proving algorithms
2. Information systems
  1. Information retrieval
  2. Information storage systems

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Published In

ACM '68: Proceedings of the 1968 23rd ACM national conference

January 1968

821 pages

ISBN:9781450374866

DOI:10.1145/800186

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]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 01 January 1968

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Cited By

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Sequeda JAllemang DJacob B(2024)A Benchmark to Understand the Role of Knowledge Graphs on Large Language Model's Accuracy for Question Answering on Enterprise SQL DatabasesProceedings of the 7th Joint Workshop on Graph Data Management Experiences & Systems (GRADES) and Network Data Analytics (NDA)10.1145/3661304.3661901(1-12)Online publication date: 14-Jun-2024
Ciatto GSabbatini FAgiollo AMagnini MOmicini A(2024)Symbolic Knowledge Extraction and Injection with Sub-symbolic Predictors: A Systematic Literature ReviewACM Computing Surveys10.1145/364510356:6(1-35)Online publication date: 8-Feb-2024
Allemang DSequeda J(2024)Increasing the Accuracy of LLM Question-Answering Systems with OntologiesThe Semantic Web – ISWC 202410.1007/978-3-031-77847-6_18(324-339)Online publication date: 27-Nov-2024
Zhao AGu ZJia YFeng WYang JZhang Y(2023)TSEE: a novel knowledge embedding framework for cyberspace securityWorld Wide Web10.1007/s11280-023-01220-926:6(4131-4152)Online publication date: 20-Dec-2023
Jia YGu ZLi AHan W(2021)Introduction to the MDATA ModelMDATA: A New Knowledge Representation Model10.1007/978-3-030-71590-8_1(1-18)Online publication date: 7-Mar-2021
Calegari RCiatto GDenti EOmicini A(2020)Logic-Based Technologies for Intelligent Systems: State of the Art and PerspectivesInformation10.3390/info1103016711:3(167)Online publication date: 22-Mar-2020
Marurngsith WWeawsawangwong P(2019)Applying Formal Logic Validation to Enhance Natural Language UnderstandingProceedings of the 2019 8th International Conference on Software and Computer Applications10.1145/3316615.3316688(380-384)Online publication date: 19-Feb-2019
Maier DTekle KKifer MWarren D(2018)DatalogDeclarative Logic Programming10.1145/3191315.3191317(3-100)Online publication date: 1-Sep-2018
Bundy ANuamah KLucas C(2018)Automated Reasoning in the Age of the InternetArtificial Intelligence and Symbolic Computation10.1007/978-3-319-99957-9_1(3-18)Online publication date: 22-Aug-2018
(2018)Declarative Logic ProgrammingundefinedOnline publication date: 1-Sep-2018
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