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Mining User Reviews with PreLM-FT Fine-Grain Sentiment Analysis |
Shen Zhuo,Li Yan() |
School of Economics and Management, Beijing Forestry University, Beijing 100083, China |
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Abstract [Objective] This paper identifies user preferences based on their reviews of the catering providers, aiming to find and improve the un-satisfactory products or services. [Methods] Firstly, we retrieved user reviews on catering industry from the DianPing website to pre-train unsupervised corpus. Then, we fine-tuned the pre-training language model with a small amount of label data. Finally, we quantified the sentiment scores of attributes from user reviews and combined the KANO model to analyze their preferences for products or services. [Results] We successfully identified user preferences with their reviews. [Limitations] The KANO model might yield some inaccurate overall preference analysis. [Conclusions] The proposed method could effectively reveal user preferences with the help of reviews and some label data.
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Received: 11 February 2019
Published: 01 June 2020
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Corresponding Authors:
Li Yan
E-mail: liyan88@bjfu.edu.cn
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