Zobrazeno 1 - 10
of 190
pro vyhledávání: '"MEME management"'
Publikováno v:
EVALITA
This paper describes the UNITOR system that participated to the “multimoDal Artefacts recogNition Knowledge for MEMES” (DANKMEMES) task within the context of EVALITA 2020. UNITOR implements a neural model which combines a Deep Convolutional Neura
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::14a4602dbaf0f019f9625b1f9293fdd2
http://hdl.handle.net/2108/269053
http://hdl.handle.net/2108/269053
Autor:
Pech, Richard J.
Publikováno v:
European Journal of Innovation Management, 2003, Vol. 6, Issue 2, pp. 111-117.
Externí odkaz:
http://www.emeraldinsight.com/doi/10.1108/14601060310475264
Conference
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Autor:
Richard J. Pech
Publikováno v:
European Journal of Innovation Management. 6:111-117
One of the major driving forces behind a firm’s success can be attributed to its meme management. Memes, analogous to the biological gene, are self‐replicating. They represent the knowledge, views, perceptions, and beliefs communicated from perso
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::594aa43303101009b7eb5dbe0d77aa59
https://doi.org/10.1108/14601060310475264
https://doi.org/10.1108/14601060310475264
Publikováno v:
The Routledge Companion to the Future of Marketing ISBN: 9780203103036
The concept of the “meme” has promised to transform our understanding of culture in the same manner as the gene has transformed our knowledge of biology. Yet, memetics has failed to live up to its promise of delivering a more complex and complete
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b13612cd8b6f891492d6fd10ad9fa3f8
https://doi.org/10.4324/9780203103036-32
https://doi.org/10.4324/9780203103036-32
Kniha
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In this paper we describe our participation to the SardiStance shared task held at EVALITA 2020. We developed a set of classifiers that combined text features, such as the best performing systems based on large pre-trained language models, together w
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=openedition_::cf559b6339176b2408af1396f1cbe0aa
http://books.openedition.org/aaccademia/7129
http://books.openedition.org/aaccademia/7129
Autor:
Delmonte, Rodolfo
In this paper we present work carried out for the Ac-ComplIt task. ItVENSES is a system for syntactic and semantic processing that is based on the parser for Italian called ItGetaruns to analyse each sentence. In previous EVALITA tasks we only used s
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=openedition_::b8218b81bc63d0447ce38d6bcd235c01
http://books.openedition.org/aaccademia/7735
http://books.openedition.org/aaccademia/7735
Autor:
De Francesco, Nazareno
The paper describes GUL.LE.VER, GUiLlottine gLovE resolVER, a Glove based system developed to solve the game “La Ghigliottina” which participated in the Evalita 2020 task Ghigliottin-AI. The system described positioned #2, with 0.26 of Precision
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=openedition_::8bb80dbe1a29ba218c8df0e36ebb6573
http://books.openedition.org/aaccademia/7500
http://books.openedition.org/aaccademia/7500
Autor:
Ou, Xiaozhi, Li, Hongling
This paper describes the system that team YNU_OXZ submitted for EVALITA 2020. We participate in the shared task on Automatic Misogyny Identification (AMI) and Hate Speech Detection (HaSpeeDe 2) at the 7th evaluation campaign EVALITA 2020. For HaSpeeD
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=openedition_::7801842c7f94b8f0459d5d0e74d9b67c
http://books.openedition.org/aaccademia/6912
http://books.openedition.org/aaccademia/6912