Expanding and Weighting Stereotypical Properties of Human Characters for Linguistic Creativity

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review


Many linguistic creativity applications rely heavily on knowledge of nouns and their properties.
However, such knowledge sources are scarce and limited.
We present a graph-based approach for expanding and weighting properties of nouns with given initial, non-weighted properties.
In this paper, we focus on famous characters, either real or fictional, and categories of people, such as Actor, Hero, Child etc.
In our case study, we started with an average of 11 and 25 initial properties for characters and categories, for which the method found 63 and 132 additional properties, respectively.
An empirical evaluation shows that the expanded properties and weights are consistent with human judgement. The resulting knowledge base can be utilized in creation of figurative language. For instance, metaphors based on famous characters can be used in various applications including story generation, creative writing, advertising and comic generation.
Original languageEnglish
Title of host publicationProceedings of the 8th International Conference on Computational Creativity (ICCC'17)
EditorsAshok Goel, Anna Jordanous, Alison Pease
Number of pages8
Place of PublicationAtlanta, GA
PublisherGeorgia Institute of Technology
Publication date23 Jun 2017
ISBN (Electronic)978-0-692-89564-1
Publication statusPublished - 23 Jun 2017
MoE publication typeA4 Article in conference proceedings
EventInternational Conference on Computational Creativity - Atlanta, United States
Duration: 19 Jun 201723 Jun 2017
Conference number: 8

Fields of Science

  • 113 Computer and information sciences
  • Artificial Intelligence
  • Computational Creativity

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