| 基于细粒度评论挖掘的书评自动摘要研究 |
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| 引用本文： | 章成志,童甜甜,周清清.基于细粒度评论挖掘的书评自动摘要研究[J].情报学报,2021(2):163-172. |
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| 作者姓名： | 章成志 童甜甜 周清清 |
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| 作者单位： | 南京理工大学信息管理系;南京师范大学网络与新媒体系 |
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| 基金项目： | 国家社会科学基金项目“融合多源异构数据的图书精准画像构建研究”(19CTQ031)。 |
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| 摘 要： | 挖掘图书评论不仅有助于用户了解图书内容,还可帮助出版社优化营销策略。图书评论摘要能够大幅提升用户获取信息的效率,用户只需简短阅读摘要即可了解评论的重点内容。如何为用户提供简洁、准确的图书评论摘要具有重要研究意义。目前的评论摘要研究多是采用句子抽取式的方法,忽视了评论中细粒度的情感信息。此外,不同的图书评论平台在评论内容方面存在较大的差异,仅基于单一平台的评论构建摘要,用户难以通过评论摘要全面了解图书。本文提出了一种包含属性信息和内容信息的图书评论摘要模型,并设计了基于细粒度评论挖掘的书评摘要方法。实证结果表明,本文提出的评论自动摘要方法,生成的评论摘要能够提供细粒度、多维度的图书评价信息。
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| 关 键 词： | 在线评论 评论挖掘 属性提取 评论自动摘要 |
Automatic Summarization of Book Reviews Based on Fine-Grained Review Mining |
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| Zhang Chengzhi,Tong Tiantian,Zhou Qingqing.Automatic Summarization of Book Reviews Based on Fine-Grained Review Mining[J].Journal of the China Society for Scientific andTechnical Information,2021(2):163-172. |
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| Authors: | Zhang Chengzhi Tong Tiantian Zhou Qingqing |
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| Institution: | (Department of Information Management,Nanjing University of Science&Technology,Nanjing 210094;Department of Network and New Media,Nanjing Normal University,Nanjing 210023) |
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| Abstract: | Mining book reviews can help users understand the content of books and help publishers optimize their marketing strategies. Book review summarization can greatly improve the efficiency of users. access to information, allowing them to quickly understand the main content of reviews by briefly reading a summary. The practice can thus provide users with concise and accurate book review summaries. Existing research on review summaries has mostly adopted methods based on sentence extraction, which neglect to address the fine-grained sentiment information in reviews. In addition, there are obvious differences in the content of reviews among different book review platforms. It is difficult for users to fully understand books through review summaries based on a single platform. In this study, we propose a book review summary model including aspect and content information and design a review summary method based on fine-grained reviews mining. The empirical results show that the review summary generated using the proposed method can provide fine-grained and multi-dimensional book evaluation information. |
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| Keywords: | online review review mining aspect extraction automatic reviews summarization |
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