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

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

9 Citations (Scopus)
12 Downloads (Pure)

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 languageEnglish
Title of host publicationProceedings of the IEEE World Congress on Computational Intelligence, 2016
Subtitle of host publicationIEEE International Conference on Fuzzy Systems FUZZ-IEEE 2016
PublisherIEEE Press
Pages587-594
Number of pages8
ISBN (Electronic)9781509006250
DOIs
Publication statusPublished - 2016
EventIEEE World Congress on Computational Intelligence, 2016 IEEE International Conference on Fuzzy Systems, - Vancouver, Canada
Duration: 24 Jul 201629 Jul 2016

Conference

ConferenceIEEE World Congress on Computational Intelligence, 2016 IEEE International Conference on Fuzzy Systems,
CountryCanada
CityVancouver
Period24/07/1629/07/16

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