An introduction to question answering with conceptRDF

Hua Chen, Antoine Trouve, K. J. Murakami, Akira Fukuda

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

With the development of information technologies, a great amount of semantic data is being generated on the web. Consequently, finding efficient ways of accessing this data becomes more and more important. Question answering is a good compromise between intuitiveness and expressivity, which has attracted the attention of researchers from different communities. In this paper, we propose an intelligent questing answering system for answering questions about concepts. It is based on ConceptRDF, which is an RDF presentation of the ConceptNet knowledge base. We use it as a knowledge base for answering questions. Our experimental results show that our approach is promising: it can answer questions about concepts at a satisfactory level of accuracy (reaches 94.5%).

Original languageEnglish
Title of host publication2017 2nd IEEE International Conference on Computational Intelligence and Applications, ICCIA 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages537-541
Number of pages5
ISBN (Electronic)9781538620304
DOIs
Publication statusPublished - Dec 4 2017
Event2nd IEEE International Conference on Computational Intelligence and Applications, ICCIA 2017 - Beijing, China
Duration: Sep 8 2017Sep 11 2017

Publication series

Name2017 2nd IEEE International Conference on Computational Intelligence and Applications, ICCIA 2017
Volume2017-January

Other

Other2nd IEEE International Conference on Computational Intelligence and Applications, ICCIA 2017
CountryChina
CityBeijing
Period9/8/179/11/17

Fingerprint

Information technology
Semantics

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Computer Science Applications

Cite this

Chen, H., Trouve, A., Murakami, K. J., & Fukuda, A. (2017). An introduction to question answering with conceptRDF. In 2017 2nd IEEE International Conference on Computational Intelligence and Applications, ICCIA 2017 (pp. 537-541). (2017 2nd IEEE International Conference on Computational Intelligence and Applications, ICCIA 2017; Vol. 2017-January). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/CIAPP.2017.8167275

An introduction to question answering with conceptRDF. / Chen, Hua; Trouve, Antoine; Murakami, K. J.; Fukuda, Akira.

2017 2nd IEEE International Conference on Computational Intelligence and Applications, ICCIA 2017. Institute of Electrical and Electronics Engineers Inc., 2017. p. 537-541 (2017 2nd IEEE International Conference on Computational Intelligence and Applications, ICCIA 2017; Vol. 2017-January).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Chen, H, Trouve, A, Murakami, KJ & Fukuda, A 2017, An introduction to question answering with conceptRDF. in 2017 2nd IEEE International Conference on Computational Intelligence and Applications, ICCIA 2017. 2017 2nd IEEE International Conference on Computational Intelligence and Applications, ICCIA 2017, vol. 2017-January, Institute of Electrical and Electronics Engineers Inc., pp. 537-541, 2nd IEEE International Conference on Computational Intelligence and Applications, ICCIA 2017, Beijing, China, 9/8/17. https://doi.org/10.1109/CIAPP.2017.8167275
Chen H, Trouve A, Murakami KJ, Fukuda A. An introduction to question answering with conceptRDF. In 2017 2nd IEEE International Conference on Computational Intelligence and Applications, ICCIA 2017. Institute of Electrical and Electronics Engineers Inc. 2017. p. 537-541. (2017 2nd IEEE International Conference on Computational Intelligence and Applications, ICCIA 2017). https://doi.org/10.1109/CIAPP.2017.8167275
Chen, Hua ; Trouve, Antoine ; Murakami, K. J. ; Fukuda, Akira. / An introduction to question answering with conceptRDF. 2017 2nd IEEE International Conference on Computational Intelligence and Applications, ICCIA 2017. Institute of Electrical and Electronics Engineers Inc., 2017. pp. 537-541 (2017 2nd IEEE International Conference on Computational Intelligence and Applications, ICCIA 2017).
@inproceedings{0504e393a1ee45b78d09c1cd65e18dee,
title = "An introduction to question answering with conceptRDF",
abstract = "With the development of information technologies, a great amount of semantic data is being generated on the web. Consequently, finding efficient ways of accessing this data becomes more and more important. Question answering is a good compromise between intuitiveness and expressivity, which has attracted the attention of researchers from different communities. In this paper, we propose an intelligent questing answering system for answering questions about concepts. It is based on ConceptRDF, which is an RDF presentation of the ConceptNet knowledge base. We use it as a knowledge base for answering questions. Our experimental results show that our approach is promising: it can answer questions about concepts at a satisfactory level of accuracy (reaches 94.5{\%}).",
author = "Hua Chen and Antoine Trouve and Murakami, {K. J.} and Akira Fukuda",
year = "2017",
month = "12",
day = "4",
doi = "10.1109/CIAPP.2017.8167275",
language = "English",
series = "2017 2nd IEEE International Conference on Computational Intelligence and Applications, ICCIA 2017",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "537--541",
booktitle = "2017 2nd IEEE International Conference on Computational Intelligence and Applications, ICCIA 2017",
address = "United States",

}

TY - GEN

T1 - An introduction to question answering with conceptRDF

AU - Chen, Hua

AU - Trouve, Antoine

AU - Murakami, K. J.

AU - Fukuda, Akira

PY - 2017/12/4

Y1 - 2017/12/4

N2 - With the development of information technologies, a great amount of semantic data is being generated on the web. Consequently, finding efficient ways of accessing this data becomes more and more important. Question answering is a good compromise between intuitiveness and expressivity, which has attracted the attention of researchers from different communities. In this paper, we propose an intelligent questing answering system for answering questions about concepts. It is based on ConceptRDF, which is an RDF presentation of the ConceptNet knowledge base. We use it as a knowledge base for answering questions. Our experimental results show that our approach is promising: it can answer questions about concepts at a satisfactory level of accuracy (reaches 94.5%).

AB - With the development of information technologies, a great amount of semantic data is being generated on the web. Consequently, finding efficient ways of accessing this data becomes more and more important. Question answering is a good compromise between intuitiveness and expressivity, which has attracted the attention of researchers from different communities. In this paper, we propose an intelligent questing answering system for answering questions about concepts. It is based on ConceptRDF, which is an RDF presentation of the ConceptNet knowledge base. We use it as a knowledge base for answering questions. Our experimental results show that our approach is promising: it can answer questions about concepts at a satisfactory level of accuracy (reaches 94.5%).

UR - http://www.scopus.com/inward/record.url?scp=85043479796&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85043479796&partnerID=8YFLogxK

U2 - 10.1109/CIAPP.2017.8167275

DO - 10.1109/CIAPP.2017.8167275

M3 - Conference contribution

AN - SCOPUS:85043479796

T3 - 2017 2nd IEEE International Conference on Computational Intelligence and Applications, ICCIA 2017

SP - 537

EP - 541

BT - 2017 2nd IEEE International Conference on Computational Intelligence and Applications, ICCIA 2017

PB - Institute of Electrical and Electronics Engineers Inc.

ER -