Development and Evaluation of a Web Based Question Answering System for Arabic Language

Kurdi, Heba; Alkhaider, Sara; Alfaifi, Nada

doi:10.5121/csit.2014.4216

Cited by 14 publications

(10 citation statements)

References 11 publications

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“… Ye s/No Arabic Question Answering System (Kurdi, et al, 2014) is a formal model for a semantic based yes/no Arabic question answering system based on paragraph retrieval. The results are based on 20 documents.…”

Section: Arabic Qa Systemsmentioning

confidence: 99%

Generating Answering Patterns from Factoid Arabic Questions

Bessaies¹,

Mesfar²,

Ghézala

2017

Proceedings of the Linguistic Resources for Automatic Natural Language Generation - LiRA@NLG

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This works deals with Arabic factoid Question Answering systems (QA). Commonly, the task of QA is divided into three phases: question analysis, answer pattern generation, and answer extraction. Each phase plays a crucial role in overall performance. In this paper, we focus on the two first phases: Question Analysis and Answer Pattern Generation. We used the NooJ platform which represents a valuable linguistic development environment. The first evaluations show that the actual results are encouraging and could be deployed for more types of questions other than factoid ones.

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Section: Arabic Qa Systemsmentioning

confidence: 99%

Generating Answering Patterns from Factoid Arabic Questions

Bessaies¹,

Mesfar²,

Ghézala

2017

Proceedings of the Linguistic Resources for Automatic Natural Language Generation - LiRA@NLG

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“…The analysis consists of three modules namely: question analysis, passage retrieval, and answer extraction. It looks for and extracts answers from the web, no knowledge base or DB is used in this system [9].…”

Section: Related Workmentioning

confidence: 99%

Developing an Intelligent Question Answering System

Ahmed¹,

Dasan²,

P³

2017

IJEME

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The goal of an intelligent answering system is that the system can respond to questions automatically. For developing such kind of system, it should be able to answer, and store these questions along with their answers. Our intelligent QA (iQA) system for Arabic language will be growing automatically when users ask new questions and the system will be accumulating these new question-answer pairs in its database. This will speed up the processing when the same question(even if it is in different syntactical structure but semantically same) is being asked again in the future. The source of knowledge of our system is the World Wide Web(WWW). The system can also understand and respond to more sophisticated questions that need a kind of temporal inference.

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“…In JAWEB [13], The question analysis module identifies the type of the question. For example (if the question begin with " ", "where"; the question type will be location).…”

Section: Fig 1: Generic Architecture Of the Typical Question Answerimentioning

confidence: 99%

“…In JAWEB [13], the answer extraction module consists of three sub-modules: answer keywords stemmer, answer similarity checker and answers ranker. The answer keywords stemmer returns the roots of the keywords in the retrieved answer.…”

Section: Fig 1: Generic Architecture Of the Typical Question Answerimentioning

confidence: 99%

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Arabic Text Question Answering from an Answer Retrieval Point of View: a survey

Sati¹,

Ali²,

Abdou³

2016

ijacsa

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Abstract-Arabic Question Answering (QA) is gaining more importance due to the importance of the language and the dramatic increase in online Arabic content. The goal of this article is to review the state-of-the-art of Arabic QA methods, to classify them into different categories from an answer retrieval viewpoint and to present their applications, issues and new trends. The main components of question answering systems are also presented. Finally, this survey provides a comparative study of systems of each type of QA based on several criteria.

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Development and Evaluation of a Web Based Question Answering System for Arabic Language

Abstract: Question Answering (QA)

Cited by 14 publications

References 11 publications

Generating Answering Patterns from Factoid Arabic Questions

Generating Answering Patterns from Factoid Arabic Questions

Developing an Intelligent Question Answering System

Arabic Text Question Answering from an Answer Retrieval Point of View: a survey

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