Abstract
This paper presents a novel answer summarization approach for community Question Answering services (cQAs) to address the problem of “incomplete answer”, i.e., missing valuable information from the “best answer” of a complex multi-sentence question, which can be obtained from other answers to the same question. Our method automatically generate a novel and non-redundant summary from cQA answers using structured determinantal point processes (SDPP). Experimental evaluation on sample dataset from Yahoo Answers shows significant improvement over baseline approaches.
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Pande, V., Mukherjee, T., Varma, V. (2013). Summarizing Answers for Community Question Answer Services. In: Gurevych, I., Biemann, C., Zesch, T. (eds) Language Processing and Knowledge in the Web. Lecture Notes in Computer Science(), vol 8105. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-40722-2_16
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DOI: https://doi.org/10.1007/978-3-642-40722-2_16
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-40721-5
Online ISBN: 978-3-642-40722-2
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