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2020 | OriginalPaper | Buchkapitel

Recognition and Analysis of Opinion Questions in Standard Arabic

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Abstract

Nowadays, most question-answering systems have been designed to answer factoid or binary questions (looking for short and precise answers such as dates, locations), however little research has been carried out to study complex questions.
In this paper, we present a method for analyzing medical opinion questions. The analysis of the question asked by the user by means of a pattern based analysis covered the syntactic as well as the morphological levels. These linguistic patterns allow us to annotate the question and the semantic features of the question by means of extracting the focus and topic of the question.
We start with the implementation of the identifying rules and the annotation of the various medical named entities. Our named entity recognizer tool (NER) is able to find references to people, places and organizations, diseases, viruses, as targets to extract the correct answer from the user. The NER is embedded in our question answering system. The task of QA is divided into four phases: question analysis, segmentation, and passage retrieval & answer extraction. Each phase plays a crucial role in the overall performance.
We use 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 further question types.

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Literatur
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Zurück zum Zitat Li, W., Ouyang, Y., Hu, Y., Wei, F.: PolyU at TAC 2008. In: Proceedings of Human Language Technologies Conference/Conference on Empirical methods in Natural Language Processing (HLT/EMNLP), Vancouver, BC, Canada (2008) Li, W., Ouyang, Y., Hu, Y., Wei, F.: PolyU at TAC 2008. In: Proceedings of Human Language Technologies Conference/Conference on Empirical methods in Natural Language Processing (HLT/EMNLP), Vancouver, BC, Canada (2008)
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Zurück zum Zitat Walaa, I., Homsi, M.: DAWQAS: a dataset for Arabic why question answering system. In: The 4th International Conference on Arabic Computational Linguistics (ACLing 2018), Dubai, United Arab Emirates, 17–19 November 2018 (2018) Walaa, I., Homsi, M.: DAWQAS: a dataset for Arabic why question answering system. In: The 4th International Conference on Arabic Computational Linguistics (ACLing 2018), Dubai, United Arab Emirates, 17–19 November 2018 (2018)
Metadaten
Titel
Recognition and Analysis of Opinion Questions in Standard Arabic
verfasst von
Essia Bessaies
Slim Mesfar
Henda Ben Ghezala
Copyright-Jahr
2020
DOI
https://doi.org/10.1007/978-3-030-38833-1_10

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