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        <title>oIQa: An Opinion Influence Oriented Question Answering Framework with Applications to Marketing Domain</title>
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    <name type="personal">
        <namePart type="given">Dumitru-Clementin</namePart>
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    <name type="personal">
        <namePart type="given">Cristian</namePart>
        <namePart type="family">Onose</namePart>
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    <name type="personal">
        <namePart type="given">Florin</namePart>
        <namePart type="family">Pop</namePart>
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            <title>Proceedings of the 1st Workshop on Natural Language Processing and Information Retrieval associated with RANLP 2017</title>
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            <namePart type="given">Mireille</namePart>
            <namePart type="family">Makary</namePart>
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    <abstract>Understanding questions and answers in QA system is a major challenge in the domain of natural language processing. In this paper, we present a question answering system that influences the human opinions in a conversation. The opinion words are quantified by using a lexicon-based method. We apply Latent Semantic Analysis and the cosine similarity measure between candidate answers and each question to infer the answer of the chatbot.</abstract>
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    <identifier type="doi">10.26615/978-954-452-038-0_002</identifier>
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%0 Conference Proceedings
%T oIQa: An Opinion Influence Oriented Question Answering Framework with Applications to Marketing Domain
%A Cercel, Dumitru-Clementin
%A Onose, Cristian
%A Trausan-Matu, Stefan
%A Pop, Florin
%Y Makary, Mireille
%Y Oakes, Michael
%S Proceedings of the 1st Workshop on Natural Language Processing and Information Retrieval associated with RANLP 2017
%D 2017
%8 September
%I INCOMA Inc.
%C Varna, Bulgaria
%F cercel-etal-2017-oiqa
%X Understanding questions and answers in QA system is a major challenge in the domain of natural language processing. In this paper, we present a question answering system that influences the human opinions in a conversation. The opinion words are quantified by using a lexicon-based method. We apply Latent Semantic Analysis and the cosine similarity measure between candidate answers and each question to infer the answer of the chatbot.
%R 10.26615/978-954-452-038-0_002
%U https://doi.org/10.26615/978-954-452-038-0_002
%P 11-18

Markdown (Informal)

[oIQa: An Opinion Influence Oriented Question Answering Framework with Applications to Marketing Domain](https://doi.org/10.26615/978-954-452-038-0_002) (Cercel et al., RANLP 2017)

• oIQa: An Opinion Influence Oriented Question Answering Framework with Applications to Marketing Domain (Cercel et al., RANLP 2017)

ACL

• Dumitru-Clementin Cercel, Cristian Onose, Stefan Trausan-Matu, and Florin Pop. 2017. oIQa: An Opinion Influence Oriented Question Answering Framework with Applications to Marketing Domain. In Proceedings of the 1st Workshop on Natural Language Processing and Information Retrieval associated with RANLP 2017, pages 11–18, Varna, Bulgaria. INCOMA Inc..