BIO Web Conf.
Volume 8, 20172016 International Conference on Medicine Sciences and Bioengineering (ICMSB2016)
|Number of page(s)||7|
|Section||Session III: Biomedical Engineering|
|Published online||11 January 2017|
An answer summarization method based on keyword extraction
Department of Computer Science, Tongji University, Shanghai, China
a Qiaoqing Fan: firstname.lastname@example.org
In order to reduce the redundancy of answer summary generated from community q&a dataset without topic tags, we propose an answer summarization algorithm based on keyword extraction. We combine tf-idf with word vector to change the influence transferred ratio equation in TextRank. And then during summarizing, we take the ratio of the number of sentences containing any keyword to the total number of candidate sentences as an adaptive factor for AMMR. Meanwhile we reuse the scores of keywords generated by TextRank as a weight factor for sentence similarity computing. Experimental results show that the proposed answer summarization is better than the traditional MMR and AMMR.
© The Authors, published by EDP Sciences, 2017
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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