Modeling Community Question-Answering Archives
نویسندگان
چکیده
Community Question Answering (CQA) services contain large archives of previously asked questions and their answers. We present a statistical topic model for modeling Question-Answering archives. The model explicitly captures relationships between questions and their answers by modeling topical dependencies. We show that the model achieves improved performance in retrieving the correct answer for a query question compared to the LDA model. Our model can also be used for automatic tagging of questions and answers. This is useful for providing topical browsing capabilities for legacy Q&A archives.
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