Expanding and Weighting Stereotypical Properties of Human Characters for Linguistic Creativity

Khalid Alnajjar, Mika Hämäläinen, Hanyang Chen, Hannu Toivonen

Tutkimustuotos: Artikkeli kirjassa/raportissa/konferenssijulkaisussaKonferenssiartikkeliTieteellinenvertaisarvioitu

Abstrakti

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.
Alkuperäiskielienglanti
OtsikkoProceedings of the 8th International Conference on Computational Creativity (ICCC'17)
ToimittajatAshok Goel, Anna Jordanous, Alison Pease
Sivumäärä8
JulkaisupaikkaAtlanta, GA
KustantajaGeorgia Institute of Technology
Julkaisupäivä23 kesäk. 2017
Sivut25-32
ISBN (elektroninen)978-0-692-89564-1
TilaJulkaistu - 23 kesäk. 2017
OKM-julkaisutyyppiA4 Artikkeli konferenssijulkaisuussa
TapahtumaInternational Conference on Computational Creativity - Atlanta, Yhdysvallat (USA)
Kesto: 19 kesäk. 201723 kesäk. 2017
Konferenssinumero: 8

Tieteenalat

  • 113 Tietojenkäsittely- ja informaatiotieteet
  • University College Dublin

    Alnajjar, K. (Vieraileva tutkija)

    8 toukok. 201622 toukok. 2016

    Aktiviteetti: Ulkoisessa instituutiossa vierailun tyypitAkateeminen vierailu toiseen organisaatioon

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