Toward an Arabic Question Answering System over Linked Data

Bouziane, Abdelghani; Bouchiha, Djelloul; Doumi, Noureddine; Malki, Mimoun

doi:10.5455/jjcit.71-1514749838

JJCIT

2018

DOI: 10.5455/jjcit.71-1514749838

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Toward an Arabic Question Answering System over Linked Data

Abdelghani Bouziane¹,

Djelloul Bouchiha²,

Noureddine Doumi³

et al.

Abstract: The increasing interest in Arabic natural language processing and semantic Web research involves an emerging need to the development of new Question Answering Systems (QAS

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2022

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Cited by 2 publications

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“…Removing the stop words: Stop words are the most common words in any language such as the, a, between, what, how.... etc. They help to build ideas but do not provide any meaning (Bouziane, Bouchiha, Doumi, & Malki, 2018). These stop words appear in many questions, so they are removed.…”

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Developing a Semantic Question Answering System for E-learning Environments using Linguistic Resources

Almotairi

Fkih²

2022

JEELR

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The Question answering (QA) system plays a basic role in the acquisition of information and the e-learning environment is considered to be the field that is most in need of the question-answering system to help learners ask questions in natural language and get answers in short periods of time. The main problem in this context is how to understand the questions without any doubts in meaning and how to provide the most relevant answers to the questions. In this study, a question-answering system for specific courses has been developed to support the learning environment. The research outcomes indicate that the proposed method helps to solve the problem of ambiguities in meaning through the integration of natural language processing tools and semantic resources that can help to overcome several problems related to the natural language structure. This method also helps improve the capability to understand students’ needs and, consequently, to retrieve the most suitable answers.

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Developing a Semantic Question Answering System for E-learning Environments using Linguistic Resources

Almotairi

Fkih²

2022

JEELR

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Inteligência artificial e ferramentas da Web Semântica aplicadas a recuperação da informação: um modelo conceitual com foco na linguagem natural

Coneglian¹,

Segundo²

2022

Inf.Inf.

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Objetivo: o artigo apresenta como objetivo a proposição de um modelo de recuperação da informação que redesenha este campo de estudos, a partir da aproximação da linguagem computacional com a linguagem natural, utilizando os princípios da representação da informação, para que o significado e o contexto dos dados estejam explícitos para o processo da busca; para tanto, aproxima-se e relaciona-se aos processos de Inteligência Artificial, processamento de linguagem natural e às ferramentas da Web Semântica.Metodologia: utilizando o método quadripolar, sendo eles: polo epistemológico, polo teórico, polo técnico e polo morfológico. Ademais, a pesquisa foi exploratória, tendo um caráter aplicado.Resultados: Como resultados, criou-se este modelo de recuperação da informação, pautado no contexto semântico e na aplicação da Inteligência Artificial, capaz de tornar a linguagem natural a base do processo, e considerando o contexto e o significado dos termos para os usuários. Conclusões: aponta-se que o presente trabalho realiza uma importante aproximação entre a Ciência da Informação e a Inteligência Artificial, trazendo para seu escopo, em especial no âmbito da recuperação da informação, aplicações reais de como este segundo campo de estudos pode aprimorar a área como um todo.

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Toward an Arabic Question Answering System over Linked Data

Abstract: The increasing interest in Arabic natural language processing and semantic Web research involves an emerging need to the development of new Question Answering Systems (QAS

Cited by 2 publications

References 26 publications

Developing a Semantic Question Answering System for E-learning Environments using Linguistic Resources

Developing a Semantic Question Answering System for E-learning Environments using Linguistic Resources

Inteligência artificial e ferramentas da Web Semântica aplicadas a recuperação da informação: um modelo conceitual com foco na linguagem natural

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