Classifying literary genres: a methodological synergy of computational modelling and lexical semantics

Abdulfattah  Omar

doi:10.35699/1983-3652.2020.24396

Autores

Abdulfattah Omar Prince Sattam Bin Abdulaziz University, Arábia Saudita / Port Said University http://orcid.org/0000-0002-3618-1750

DOI:

https://doi.org/10.35699/1983-3652.2020.24396

Palavras-chave:

Bolsa de conceitos (COB), ConceptNet, Análise Semântica Explícita (ASE), Classificação de gênero, Conceitos de tópicos, Vector Space Clustering (VSC)

Resumo

A classificação de gêneros literários sempre se restringiu metodologicamente aos métodos filológicos e ao que é comumente conhecido como Vector Space Clustering (VSC). O problema foi exasperado com a crescente lacuna entre a teoria computacional e a análise tradicional de textos literários. Para encontrar uma solução para esse problema, o presente estudo utiliza uma abordagem sinérgica que reúne dois métodos estabelecidos. Primeiro, um modelo computacional de classificação de gênero é utilizado para identificar tópicos baseados em conceito, em vez de vinculados a palavras, em que a representação de textos é protegida por meio do modelo “bolsa de conceitos” (BOC), bem como o conhecimento restrito aos sentidos e os vínculos significativos entre os conceitos; De maneira semelhante, os dois modelos de análise semântica explícita (ASE) e ConceptNet promulgaram a classificação do texto. Segundo, uma abordagem semântica lexical contextual (CRUSE, 1986, 2000) é empregada para que a variabilidade contextual dos significados e conceitos das palavras possa ser abordada dentro dos limites dos gêneros literários alvo classificados. As descobertas do presente estudo mostraram que a atual abordagem composta de modelos computacionais e semânticos resultou em melhor desempenho na classificação de gêneros literários, especialmente no que diz respeito a delinear os vínculos entre os membros do documento de cada grupo e generalizar sobre seu gênero unificador. Outras implicações emergiram do presente estudo, a saber, os benefícios reservados para as bibliotecas digitais e o processo de arquivamento, em que a classificação de textos literários se mostrou problemática para usuários e leitores em muitos casos.

Biografia do Autor

Abdulfattah Omar, Prince Sattam Bin Abdulaziz University, Arábia Saudita / Port Said University

Professor associado de linguística na Universidade Prince Sattam Bin Abdulaziz. Terminou seu doutorado em linguística na Universidade de Newcastle em 2010. Seus interesses de pesquisa incluem linguística computacional, humanidades digitais e computação literária.

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