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  • Open Access

    ARTICLE

    Deep Learning and Machine Learning-Based Model for Conversational Sentiment Classification

    Sami Ullah1, Muhammad Ramzan Talib1,*, Toqir A. Rana2,3, Muhammad Kashif Hanif1, Muhammad Awais4

    CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 2323-2339, 2022, DOI:10.32604/cmc.2022.025543

    Abstract In the current era of the internet, people use online media for conversation, discussion, chatting, and other similar purposes. Analysis of such material where more than one person is involved has a spate challenge as compared to other text analysis tasks. There are several approaches to identify users’ emotions from the conversational text for the English language, however regional or low resource languages have been neglected. The Urdu language is one of them and despite being used by millions of users across the globe, with the best of our knowledge there exists no work on dialogue analysis in the Urdu… More >

  • Open Access

    ARTICLE

    Extraction of Opinion Target Using Syntactic Rules in Urdu Text

    Toqir A. Rana1,*, Bahrooz Bakht1, Mehtab Afzal1, Natash Ali Mian2, Muhammad Waseem Iqbal3, Abbas Khalid1, Muhammad Raza Naqvi4

    Intelligent Automation & Soft Computing, Vol.29, No.3, pp. 839-853, 2021, DOI:10.32604/iasc.2021.018572

    Abstract Opinion target or aspect extraction is the key task of aspect-based sentiment analysis. This task focuses on the extraction of targeted words or phrases against which a user has expressed his/her opinion. Although, opinion target extraction has been studied extensively in the English language domain, with notable work in other languages such as Chinese, Arabic etc., other regional languages have been neglected. One of the reasons is the lack of resources and available texts for these languages. Urdu is one, with millions of native and non-native speakers across the globe. In this paper, the Urdu language domain is focused on… More >

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