Topic Mining Based on Online Shopping Users' Reviews

机译：基于网购用户评论的主题挖掘

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Digging into the potential features of user comments is of great significance to optimize product design and enhance market competitiveness. Taking baby pacifiers as an example, this paper uses the user review data on Amazon platform to extract the topic

机译：挖掘用户评论的潜在特征对于优化产品设计和增强市场竞争力具有重要意义。以婴儿奶嘴为例，本文使用Amazon平台上的用户评论数据提取主题

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《International Conference on Computer Information and Big Data Applications》|2020年|11-14|共4页
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作者
Ying Wang; Manqi Jiang;
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topic mining; user review; topic intensity; LDA model;

机译：主题挖掘;用户评论;主题强度; LDA模型;

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1. User Needs Mining Based on Topic Analysis of Online Reviews [J] . Liu Liqiong, Zhang Liyi, Ye Pinghao, Technical Gazette . 2019,第1期

机译：基于在线评论主题分析的用户需求挖掘
2. Exploring hidden factors behind online food shopping from Amazon reviews: A topic mining approach [J] . Yan Heng, Zhifeng Gao, Yuan Jiang, Journal of retailing and consumer services . 2018,第may期

机译：探索来自亚马逊评论的在线食品购物背后的隐藏因素：一种主题挖掘方法
3. Users' interest grouping from online reviews based on topic frequency and order [J] . Jianfeng Si, Qing Li, Tieyun Qian, World Wide Web . 2014,第6期

机译：基于主题频率和顺序的在线评论中的用户兴趣分组
4. A Novel Perspective to Mining Online Hotel Reviews Based on Biterm Topic Model [C] . Qianqian Ma, Huiying Du, Zhiyuan Wang IEEE International Conference on Big Data Analytics . 2021

机译：基于Biterm主题模型的小说挖掘在线酒店评价
5. The online shopping and purchasing behavior of Millennials who rely on online reviews: A qualitative study. [D] . Burger, Rachel A. 2014

机译：依赖在线评论的千禧一代的在线购物和购买行为：定性研究。
6. Male and Female Users’ Differences in Online Technology Community Based on Text Mining [O] . Bing Sun, Hongying Mao, Chengshun Yin 2020

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7. Text mining of online book reviews for non-trivial clustering of books and users [O] . Lin Eric 2013

机译：在线书评的文本挖掘，用于书和用户的非平凡聚类

Topic Mining Based on Online Shopping Users' Reviews

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