It is necessary to extract product attributes and calculate product attribute weights through online reviews of products. On this basis, alternative products can be ranked through the product ranking method. The obtained ranking results can help consumers to select alternatives.
Sep 3, 2021
Dec 9, 2024 · Using the online review data to help customers make purchasing decisions has become a concern of customers, which has theoretical and practical ...
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We propose a method for extracting product attributes from online reviews by using the Term Frequency-Inverse Document Frequency (TF-IDF) algorithm.
Fu et al. put forward a method of product ranking by combining feature opinion mining with interval ratio Pythagorean fuzzy sets [42].
First， the utility values of the online reviews are calculated. By extracting the product attributes， the attribute set for product selection is obtained.
Feb 20, 2022 · “The IF-TODIM method for product ranking based on online review” develops a new IF-TODIM method for product selection based on online reviews.
Sep 2, 2021 · Then a method for representing the sentiment analysis results of online reviews in the form of linguistic distribution is proposed.
Product selection based on sentiment analysis of online reviews: an intuitionistic fuzzy TODIM method. Language: English; Authors: Zhang, Zhenyu1 (AUTHOR)
Firstly, the Apriori algorithm is used to extract the product features that customers focus on based on online reviews.
This hybrid method assists potential customers in evaluating alternative products by considering consumer opinions regarding product performance in the 2-tuple ...