An Exploratory Study on the Benefits of using Natural Language for Explaining Fuzzy Rule-based Systems

Jose Alonso; Alejandro Ramos Soto; Ehud Baruch Reiter; Kees van Deemter

doi:10.1109/FUZZ-IEEE.2017.8015489

An Exploratory Study on the Benefits of using Natural Language for Explaining Fuzzy Rule-based Systems

Jose Alonso, Alejandro Ramos Soto, Ehud Baruch Reiter, Kees van Deemter

Computing Science

Research output: Chapter in Book/Report/Conference proceeding › Published conference contribution

19 Citations (Scopus)

Abstract

This paper presents an empirical research. It focuses on testing empirically the benefits of providing users, in a specific domain, with textual interpretation of the fuzzy inferences carried out by a fuzzy classifier for a given selection of samples. The hypothesis to test is as follows: “Users understand easier the
decision made by a fuzzy system when they are provided with a textual interpretation of the fuzzy inference mechanism that the system carried out”. This hypothesis was successfully tested in a web survey. The application domain was leaf classification. The fuzzy classifiers were built with the GUAJE fuzzy modeling open source software which is aimed at generating interpretable fuzzy
systems. The textual interpretation was handmade by an expert who followed the guidelines of the Natural Language Generation approach proposed by Reiter and Dale. Reported results encourage us to go on with a series of additional experiments devoted to deeply explore how Natural Language Generation techniques can contribute to facilitate the understanding of fuzzy systems.

Original language	English
Title of host publication	2017 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)
Publisher	IEEE Explore
Pages	1-6
Number of pages	6
ISBN (Electronic)	9781509060344
ISBN (Print)	9781509060351
DOIs	https://doi.org/10.1109/FUZZ-IEEE.2017.8015489
Publication status	Published - Dec 2017
Event	IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), 2017 - Naples, Italy Duration: 9 Jul 2017 → 12 Jul 2017

Publication series

Name
ISSN (Electronic)	1558-4739

Conference

Conference	IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), 2017
Abbreviated title	(FUZZ-IEEE)
Country/Territory	Italy
City	Naples
Period	9/07/17 → 12/07/17

Access to Document

10.1109/FUZZ-IEEE.2017.8015489Licence: Unspecified

Ehud Reiter
- Computational Linguistics at Aberdeen
- School of Medicine, Medical Sciences & Nutrition, Centre for Health Data Science
- School of Natural & Computing Sciences, Computing Science - Chair in Computing Science.
Person: Academic

Cite this

Alonso, J, Ramos Soto, A, Reiter, EB & van Deemter, K 2017, An Exploratory Study on the Benefits of using Natural Language for Explaining Fuzzy Rule-based Systems. in 2017 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE). IEEE Explore, pp. 1-6, IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), 2017, Naples, Italy, 9/07/17. https://doi.org/10.1109/FUZZ-IEEE.2017.8015489

@inproceedings{6dccf5caa38946c3bafee7a9f9ba3c45,

title = "An Exploratory Study on the Benefits of using Natural Language for Explaining Fuzzy Rule-based Systems",

abstract = "This paper presents an empirical research. It focuses on testing empirically the benefits of providing users, in a specific domain, with textual interpretation of the fuzzy inferences carried out by a fuzzy classifier for a given selection of samples. The hypothesis to test is as follows: “Users understand easier thedecision made by a fuzzy system when they are provided with a textual interpretation of the fuzzy inference mechanism that the system carried out”. This hypothesis was successfully tested in a web survey. The application domain was leaf classification. The fuzzy classifiers were built with the GUAJE fuzzy modeling open source software which is aimed at generating interpretable fuzzysystems. The textual interpretation was handmade by an expert who followed the guidelines of the Natural Language Generation approach proposed by Reiter and Dale. Reported results encourage us to go on with a series of additional experiments devoted to deeply explore how Natural Language Generation techniques can contribute to facilitate the understanding of fuzzy systems.",

author = "Jose Alonso and {Ramos Soto}, Alejandro and Reiter, {Ehud Baruch} and {van Deemter}, Kees",

note = "This work has been funded by TIN2014-56633-C3-1-R and TIN2014-56633-C3-3-R projects from the Spanish “Ministerio de Economıa y Competitividad” and by the “Consellerıa de Cultura, Educacion e Ordenacion Universitaria” (accreditation 2016-2019, ED431G/08) and the European Regional Development Fund (ERDF). In addition, we would like to thank FLAVIA project. Moreover, we would like to thank all anonymous subjects who took part in the web survey.; IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), 2017, (FUZZ-IEEE) ; Conference date: 09-07-2017 Through 12-07-2017",

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N1 - This work has been funded by TIN2014-56633-C3-1-R and TIN2014-56633-C3-3-R projects from the Spanish “Ministerio de Economıa y Competitividad” and by the “Consellerıa de Cultura, Educacion e Ordenacion Universitaria” (accreditation 2016-2019, ED431G/08) and the European Regional Development Fund (ERDF). In addition, we would like to thank FLAVIA project. Moreover, we would like to thank all anonymous subjects who took part in the web survey.

PY - 2017/12

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N2 - This paper presents an empirical research. It focuses on testing empirically the benefits of providing users, in a specific domain, with textual interpretation of the fuzzy inferences carried out by a fuzzy classifier for a given selection of samples. The hypothesis to test is as follows: “Users understand easier thedecision made by a fuzzy system when they are provided with a textual interpretation of the fuzzy inference mechanism that the system carried out”. This hypothesis was successfully tested in a web survey. The application domain was leaf classification. The fuzzy classifiers were built with the GUAJE fuzzy modeling open source software which is aimed at generating interpretable fuzzysystems. The textual interpretation was handmade by an expert who followed the guidelines of the Natural Language Generation approach proposed by Reiter and Dale. Reported results encourage us to go on with a series of additional experiments devoted to deeply explore how Natural Language Generation techniques can contribute to facilitate the understanding of fuzzy systems.

AB - This paper presents an empirical research. It focuses on testing empirically the benefits of providing users, in a specific domain, with textual interpretation of the fuzzy inferences carried out by a fuzzy classifier for a given selection of samples. The hypothesis to test is as follows: “Users understand easier thedecision made by a fuzzy system when they are provided with a textual interpretation of the fuzzy inference mechanism that the system carried out”. This hypothesis was successfully tested in a web survey. The application domain was leaf classification. The fuzzy classifiers were built with the GUAJE fuzzy modeling open source software which is aimed at generating interpretable fuzzysystems. The textual interpretation was handmade by an expert who followed the guidelines of the Natural Language Generation approach proposed by Reiter and Dale. Reported results encourage us to go on with a series of additional experiments devoted to deeply explore how Natural Language Generation techniques can contribute to facilitate the understanding of fuzzy systems.

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BT - 2017 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)

PB - IEEE Explore

T2 - IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), 2017

Y2 - 9 July 2017 through 12 July 2017

ER -

An Exploratory Study on the Benefits of using Natural Language for Explaining Fuzzy Rule-based Systems

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