Natural Language Generation and Fuzzy Sets: An Exploratory Study on Geographical Referring Expression Generation

Alejandro  Ramos-Soto; Nava Tintarev; Rodrigo De Oliveira; Ehud Reiter; Kees van Deemter

doi:10.1109/FUZZ-IEEE.2016.7737740

Natural Language Generation and Fuzzy Sets: An Exploratory Study on Geographical Referring Expression Generation

Alejandro Ramos-Soto, Nava Tintarev, Rodrigo De Oliveira, Ehud Reiter, Kees van Deemter

Computing Science

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

10 Citations (Scopus)

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Abstract

We explore how the problem of uncertainty and imprecision in natural language generation (NLG) could be addressed through the use of fuzzy sets. We propose bringing together standard empirical procedures for knowledge acquisition in NLG and computing with words/perceptions related techniques (with a special focus on linguistic description of data) to address an open challenge in NLG: the generation of geographical referring expressions. Following this methodology, we present an exploratory experiment which provides some insights about how human subjects refer to geographical expressions and discuss how the obtained results might relate to the use of fuzzy sets.

Original language	English
Title of host publication	Proceedings of the IEEE World Congress on Computational Intelligence, 2016
Subtitle of host publication	IEEE International Conference on Fuzzy Systems FUZZ-IEEE 2016
Publisher	IEEE Press
Pages	587-594
Number of pages	8
ISBN (Electronic)	9781509006250
DOIs	https://doi.org/10.1109/FUZZ-IEEE.2016.7737740
Publication status	Published - 2016
Event	IEEE World Congress on Computational Intelligence, 2016 IEEE International Conference on Fuzzy Systems, - Vancouver, Canada Duration: 24 Jul 2016 → 29 Jul 2016

Conference

Conference	IEEE World Congress on Computational Intelligence, 2016 IEEE International Conference on Fuzzy Systems,
Country/Territory	Canada
City	Vancouver
Period	24/07/16 → 29/07/16

Bibliographical note

This work was supported by the Spanish Ministry for Economy and Competitiveness (grant TIN2014-56633-C3-1-R) and by the European Regional Development Fund (ERDF/FEDER) and the Galician Ministry of Education (grants GRC2014/030 and CN2012/151). Alejandro Ramos-Soto is supported by the Spanish Ministry for Economy and Competitiveness (FPI Fellowship Program) under grant BES-2012-051878.

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Accepted author manuscript, 4.16 MBLicence: Unspecified

Cite this

Ramos-Soto, A., Tintarev, N., De Oliveira, R., Reiter, E., & van Deemter, K. (2016). Natural Language Generation and Fuzzy Sets: An Exploratory Study on Geographical Referring Expression Generation. In Proceedings of the IEEE World Congress on Computational Intelligence, 2016 : IEEE International Conference on Fuzzy Systems FUZZ-IEEE 2016 (pp. 587-594). Article 7737740 IEEE Press. https://doi.org/10.1109/FUZZ-IEEE.2016.7737740

Natural Language Generation and Fuzzy Sets: An Exploratory Study on Geographical Referring Expression Generation. / Ramos-Soto, Alejandro ; Tintarev, Nava; De Oliveira, Rodrigo et al.
Proceedings of the IEEE World Congress on Computational Intelligence, 2016 : IEEE International Conference on Fuzzy Systems FUZZ-IEEE 2016. IEEE Press, 2016. p. 587-594 7737740.

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

Ramos-Soto, A, Tintarev, N, De Oliveira, R, Reiter, E & van Deemter, K 2016, Natural Language Generation and Fuzzy Sets: An Exploratory Study on Geographical Referring Expression Generation. in Proceedings of the IEEE World Congress on Computational Intelligence, 2016 : IEEE International Conference on Fuzzy Systems FUZZ-IEEE 2016., 7737740, IEEE Press, pp. 587-594, IEEE World Congress on Computational Intelligence, 2016 IEEE International Conference on Fuzzy Systems, Vancouver, Canada, 24/07/16. https://doi.org/10.1109/FUZZ-IEEE.2016.7737740

Ramos-Soto A, Tintarev N, De Oliveira R, Reiter E, van Deemter K. Natural Language Generation and Fuzzy Sets: An Exploratory Study on Geographical Referring Expression Generation. In Proceedings of the IEEE World Congress on Computational Intelligence, 2016 : IEEE International Conference on Fuzzy Systems FUZZ-IEEE 2016. IEEE Press. 2016. p. 587-594. 7737740 Epub 2016 Nov 10. doi: 10.1109/FUZZ-IEEE.2016.7737740

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abstract = "We explore how the problem of uncertainty and imprecision in natural language generation (NLG) could be addressed through the use of fuzzy sets. We propose bringing together standard empirical procedures for knowledge acquisition in NLG and computing with words/perceptions related techniques (with a special focus on linguistic description of data) to address an open challenge in NLG: the generation of geographical referring expressions. Following this methodology, we present an exploratory experiment which provides some insights about how human subjects refer to geographical expressions and discuss how the obtained results might relate to the use of fuzzy sets.",

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Natural Language Generation and Fuzzy Sets: An Exploratory Study on Geographical Referring Expression Generation

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