An Empirical Approach for Modeling Fuzzy Geographical Descriptors

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

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

2 Citations (Scopus)

Abstract

We present a novel heuristic approach that defines fuzzy geographical descriptors using data gathered from a survey with human subjects. The participants were asked to provide graphical interpretations of the descriptors ‘north’ and ‘south’ for the Galician region (Spain). Based on these interpretations, our approach builds fuzzy descriptors that are able to compute membership degrees for geographical locations. We evaluated our approach in terms of efficiency and precision. The fuzzy descriptors are meant to be used as the cornerstones of a geographical referring expression generation algorithm that is able to linguistically characterize
geographical locations and regions. This work is also part of a general research effort that intends to establish a methodology which reunites the empirical studies traditionally practiced in data-to-text and the use of fuzzy sets to model imprecision and vagueness in words and expressions for text generation purposes
Original languageEnglish
Title of host publication2017 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)
PublisherIEEE Explore
Pages1-6
Number of pages6
ISBN (Electronic)978-1-5090-6034-4
DOIs
Publication statusPublished - 2017
EventIEEE International Conference on Fuzzy Systems (FUZZ-IEEE), 2017 - Naples, Italy
Duration: 9 Jul 201712 Jul 2017

Conference

ConferenceIEEE International Conference on Fuzzy Systems (FUZZ-IEEE), 2017
Abbreviated title(FUZZ-IEEE)
CountryItaly
CityNaples
Period9/07/1712/07/17

Fingerprint

Fuzzy sets

Cite this

Ramos Soto, A., Alonso, J., Reiter, E. B., van Deemter, K., & Gatt, A. (2017). An Empirical Approach for Modeling Fuzzy Geographical Descriptors. In 2017 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE) (pp. 1-6). IEEE Explore. https://doi.org/10.1109/FUZZ-IEEE.2017.8015527

An Empirical Approach for Modeling Fuzzy Geographical Descriptors. / Ramos Soto, Alejandro; Alonso, Jose; Reiter, Ehud Baruch; van Deemter, Kees; Gatt, Albert.

2017 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE). IEEE Explore, 2017. p. 1-6.

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

Ramos Soto, A, Alonso, J, Reiter, EB, van Deemter, K & Gatt, A 2017, An Empirical Approach for Modeling Fuzzy Geographical Descriptors. 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.2017.8015527
Ramos Soto A, Alonso J, Reiter EB, van Deemter K, Gatt A. An Empirical Approach for Modeling Fuzzy Geographical Descriptors. In 2017 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE). IEEE Explore. 2017. p. 1-6 https://doi.org/10.1109/FUZZ-IEEE.2017.8015527
Ramos Soto, Alejandro ; Alonso, Jose ; Reiter, Ehud Baruch ; van Deemter, Kees ; Gatt, Albert. / An Empirical Approach for Modeling Fuzzy Geographical Descriptors. 2017 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE). IEEE Explore, 2017. pp. 1-6
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abstract = "We present a novel heuristic approach that defines fuzzy geographical descriptors using data gathered from a survey with human subjects. The participants were asked to provide graphical interpretations of the descriptors ‘north’ and ‘south’ for the Galician region (Spain). Based on these interpretations, our approach builds fuzzy descriptors that are able to compute membership degrees for geographical locations. We evaluated our approach in terms of efficiency and precision. The fuzzy descriptors are meant to be used as the cornerstones of a geographical referring expression generation algorithm that is able to linguistically characterizegeographical locations and regions. This work is also part of a general research effort that intends to establish a methodology which reunites the empirical studies traditionally practiced in data-to-text and the use of fuzzy sets to model imprecision and vagueness in words and expressions for text generation purposes",
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