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一种基于深度学习的电子商务满意度评估方法 被引量:5

An E-Commerce Satisfaction Evaluation Method Based on Deep Learning
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摘要 随着电子商务的崛起,越来越多的消费者选择通过网购来获取所需的商品。消费者评论信息中包含了对商品、物流等电子商务各方面的满意程度,这就使得在线商品评论信息成为研究电子商务满意度的重要参考依据。因此充分分析商品评论中的消费者满意程度,具有巨大的商业价值和社会价值。本文从意见挖掘的角度出发,提出了一种基于深度学习的电子商务满意度评估方法,旨在为消费者进行网购决策时提供一些指导建议。 With the rise of e-commerce,more and more consumers have chosen to acquire the required products through online shopping.The consumer review information includes the degree of satisfaction with various aspects of e-commerce such as commodities and logistics,which makes online product review information an important reference for research on e-commerce satisfaction.Therefore,a full analysis of consumer satisfaction in commodity reviews has enormous commercial and social value.From the perspective of opinion mining,this paper proposes an evaluation method for e-commerce satisfaction based on deep learning,which aims to provide some suggestions for consumers when making online shopping decisions.
作者 王红梅 WANG Hongmai(Nanjing College of Information Technology,Nanjing 210013,China)
出处 《电子器件》 CAS 北大核心 2020年第1期196-199,共4页 Chinese Journal of Electron Devices
基金 2016年江苏省高校哲学社会科学研究指导项目(2016SJD880037)。
关键词 电子商务满意度 意见挖掘 深度学习 E-commerce satisfaction opinion mining deep learning
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  • 1查金祥,王立生.网络购物顾客满意度影响因素的实证研究[J].管理科学,2006,19(1):50-58. 被引量:219
  • 2王传美,鲁耀斌,童恒庆.基于SEM的B2C电子商务信任评价模型及算法[J].南开管理评论,2006,9(6):104-108. 被引量:18
  • 3中国互联网络信息中心.中国互联网络发展状况统计报告[R].2010.
  • 4Franco Salvetti, Stephen Lewis, Christoph Reichenbach. Automatic Opinion Polarity Classification of Movie Reviews[J]. Colorado Research in Linguistics, 2004, Volume 17, Issue 1.
  • 5Bo Pang, Lillian Lee, and Shivakumar Vaithyanathan. Thumbs up? Sentiment classification using machine learning techniques[A]. In: Proceedings of the 2002 Conference on Empirical Methods in Natural Language Processing (EMNLP), pages 79 86.
  • 6Aidan Finn, Nicholas Kushmerick, and Barry Smyth. Genre classification and domain transfer for information filtering[A]. In: Fabio Crestani, Mark Girolami, and Cornelis J. van Rijsbergen, editors, Proceedings of ECIR-02, 24th European Colloquium on Information Retrieval Research, Glasgow, UK. Springer Verlag, Heidelberg, DE.
  • 7Janyce Wiebe, Rebecca Bruce, Matthew Bell, Melanie Martin, and Theresa Wilson. A corpus study of evaluative and speculative language[A]. In: Proceedings of the 2nd ACL SIGdial Workshop on Discourse and Dialogue, 2001.
  • 8Alina Andreevskaia and Sabine Bergler. Mining Word-Net For a Fuzzy Sentiment: Sentiment Tag Extraction From WordNet Glosses[A].In: Proc. EACL-06, Trento, Italy, 2006.
  • 9Alistair Kennedy and Diana Inkpen. Sentiment Classification of Movie Reviews Using Contextual Valence Shifters[J]. Computational Intelligence, 2006,22 (2) 110-125.
  • 10P.D. Turney and M.L. Littman. Unsupervised learning of semantic orientation from a hundred-billion-word corpus[D]. Technical Report ERB-1094, National Research Council Canada, Institute for Information Technology, 2002.

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