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| Automatic Summarization of Book Reviews Based on Fine-Grained Review Mining |
| Zhang Chengzhi1, Tong Tiantian1, Zhou Qingqing2 |
1.Department of Information Management, Nanjing University of Science & Technology, Nanjing 210094
2.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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Received: 04 December 2019
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