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JokeMeter at SemEval-2020 Task 7: Convolutional Humor

Result description

This paper describes our system that was designed for Humor evaluation within the SemEval-2020 Task 7. The system is based on convolutional neural network architecture. We investigate the system on the official dataset, and we provide more insight to model itself to see how the learned inner features look.

Keywords

convolutional neural networksCNNhumorfunninessconvolutionassessing humorestimating the humorestimating the funniness

The result's identifiers

Alternative languages

  • Result language

    angličtina

  • Original language name

    JokeMeter at SemEval-2020 Task 7: Convolutional Humor

  • Original language description

    This paper describes our system that was designed for Humor evaluation within the SemEval-2020 Task 7. The system is based on convolutional neural network architecture. We investigate the system on the official dataset, and we provide more insight to model itself to see how the learned inner features look.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

  • OECD FORD branch

    10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Result continuities

Others

  • Publication year

    2020

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Article name in the collection

    Proceedings of the Fourteenth Workshop on Semantic Evaluation

  • ISBN

    978-1-952148-31-6

  • ISSN

  • e-ISSN

  • Number of pages

    9

  • Pages from-to

    843-851

  • Publisher name

    Association for Computational Linguistics

  • Place of publication

    Barcelona (online)

  • Event location

    Barcelona (online)

  • Event date

    Dec 8, 2020

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article

Basic information

Result type

D - Article in proceedings

D

OECD FORD

Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Year of implementation

2020