Arabic Language Challenges in Text Based Conversational Agents Compared to The English Language

Hijjawi, Mohammad; Elsheikh, Yousef

doi:10.5121/ijcsit.2015.7301

Cited by 14 publications

(12 citation statements)

References 19 publications

(38 reference statements)

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“…There are two formal varieties of Arabic, known in English as Classical Arabic, and Modern Standard Arabic (MSA) and one informal variety of Arabic called colloquial Arabic (dialect). Firstly, Classical Arabic, is known as the original language of the Qur'an and it was used in the era before Islam (Hijjawi & Elsheikh, 2015). Classical Arabic is used for religious and ceremonial purposes.…”

Section: Literature Reviewmentioning

confidence: 99%

Arabic Is the Language of ‘Ahlul-Jannah’ (People of Paradise): The Religious Status of Arabic Language Contributes to Its Maintenance

2018

APJABSS

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This paper attempts to investigate the impact of the religious status of the Arabic language and to find out to what extent this status contributes to its maintenance within the Arabicspeaking community in the regional Queensland city of Toowoomba, Australia. A qualitative approach was employed in order to explore the language maintenance phenomenon through engaging in the everyday life of the Arabic speakers. Data was gathered through participant observations and in-depth semi-structured interviews with 20 adults who were selected using a mixed purposeful sampling strategy. The findings of this study reveal that the Arabic language is maintained among the Arabic speakers due to the high exalted status that Arabic holds as a language of Islam which represents the Arab and Muslim identity. The conclusions of this study are envisaged to enrich the knowledge and theories of language maintenance, as well as redesigning the multilingualism and multiculturalism structure of the Australian society.

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Section: Literature Reviewmentioning

confidence: 99%

Arabic Is the Language of ‘Ahlul-Jannah’ (People of Paradise): The Religious Status of Arabic Language Contributes to Its Maintenance

2018

APJABSS

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“…Chatbots mimic human conversation [2]. While English language dialogue systems have been proven stable and accurate, 97% of current dialogue systems are unsuitable for use with Arabic [3].…”

Section: Introductionmentioning

confidence: 99%

Mining the Chatbot Brain to Improve COVID-19 Bot Response Accuracy

Ghaleb¹,

Almurtadha²,

Algarni³

et al. 2022

Computers, Materials &Amp; Continua

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People often communicate with auto-answering tools such as conversational agents due to their 24/7 availability and unbiased responses. However, chatbots are normally designed for specific purposes and areas of experience and cannot answer questions outside their scope. Chatbots employ Natural Language Understanding (NLU) to infer their responses. There is a need for a chatbot that can learn from inquiries and expand its area of experience with time. This chatbot must be able to build profiles representing intended topics in a similar way to the human brain for fast retrieval. This study proposes a methodology to enhance a chatbot's brain functionality by clustering available knowledge bases on sets of related themes and building representative profiles. We used a COVID-19 information dataset to evaluate the proposed methodology. The pandemic has been accompanied by an "infodemic" of fake news. The chatbot was evaluated by a medical doctor and a public trial of 308 real users. Evaluations were obtained and statistically analyzed to measure effectiveness, efficiency, and satisfaction as described by the ISO9214 standard. The proposed COVID-19 chatbot system relieves doctors from answering questions. Chatbots provide an example of the use of technology to handle an infodemic.

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“…It should be noted that these methods can be modified to another language, such as Arabic. The Arabic language did not receive the effort that other languages did [6]. However, several studies of sentiment analysis of Arabic writing have been proposed [7].…”

Section: Introductionmentioning

confidence: 99%

An Improved Arabic Sentiment Analysis Approach using Optimized Multinomial Naïve Bayes Classifier

Alsanad¹

2022

IJACSA

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Arabic sentiment analysis has emerged during the last decade as a computational process on Arabic texts for extracting people's attitudes toward targeted objects or their feelings and emotions regarding targeted events. Sentiment analysis (SA) using machine learning (ML) methods has become an important research task for developing various text-based applications. Among different ML classifiers, multinomial Naïve Bayes (MNNB) classifier is widely used for documents classification due to its ability for performing statistical analysis of text contents. It significantly simplifies textual-data classification and offers an alternative to heavy ML-based semantic analysis methods. However, the MNNB classifier has a number of hyper-parameters affects the classification task of texts and controls the decision boundary of the model itself. In this paper, an optimized MNNB classifier-based approach is proposed for improving Arabic sentiment analysis. A number of experiments are conducted on large sets of Arabic tweets to evaluate the proposed approach. The optimized MNNB classifier is trained on three datasets and tested on a different separated test set to show the performance of developed approach. The experimental results on the test set revealed that the optimized MNNB classifier of proposed approach outperforms the traditional MNNB classifier and other baseline classifiers. The accuracy rate of the optimization approach is increased by 1.6% compared with using the default values of the classifier's hyperparameters.

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Arabic Language Challenges in Text Based Conversational Agents Compared to The English Language

Abstract: ABSTRACT

Cited by 14 publications

References 19 publications

Arabic Is the Language of ‘Ahlul-Jannah’ (People of Paradise): The Religious Status of Arabic Language Contributes to Its Maintenance

Arabic Is the Language of ‘Ahlul-Jannah’ (People of Paradise): The Religious Status of Arabic Language Contributes to Its Maintenance

Mining the Chatbot Brain to Improve COVID-19 Bot Response Accuracy

An Improved Arabic Sentiment Analysis Approach using Optimized Multinomial Naïve Bayes Classifier

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