由于大量的游客在社交媒体上记录自己的心情,人们在享受便捷获取网络上大量旅游信息的同时,也淹没在混乱的游记信息海洋里。为了从游记中获取游客关心的景点信息和游客对景点表达的情感信息,该文提出了一个多文档游记的情感摘要生成方法,该方法结合指针生成网络和最大边界相关算法,构建了一个端到端的神经网络摘要生成模型。该模型在进行文本摘要生成时,对于情感信息给予重视,使得生成的摘要包含一定的情感信息。通过在自建数据集上进行训练和测试,实验结果验证了该模型的有效性。
Abstract
A large number of tourists record their mood on social media, with abundant tourists' emotional information about the scenic spot in their travel notes. To provide better scenic spot information, this paper proposes a emotional summary method for multiple scenic spot travel notes. It combines the pointer generation network and the maximum boundary correlation algorithm to build an end-to-end neural network summary generation model. The proposed model attaches importance to the emotional information while abstracting the text. The experimental results show that the proposed model is effective on a self-built data set.
关键词
旅游 /
文本摘要生成 /
情感信息
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Key words
tourism /
text summarization generation /
emotional information
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脚注
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基金
国家自然科学基金(62076158,62072294,61906112);山西省重点研发计划项目(201803D421024);山西省应用基础研究计划项目(201901D211174); 山西省高等学校科技创新项目(2019L0008, 2020L0001)
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