oIQa: An Opinion Influence Oriented Question Answering Framework with Applications to Marketing Domain

Understanding questions and answers in Question Answering (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 bot.

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