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Published in:
2021 | OriginalPaper | Chapter
E-commerce Review Classification Based on SVM
Authors : Qiaohong Zu, Yang Zhou, Wei Zhu
Published in: Human Centered Computing
Publisher: Springer International Publishing
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Abstract
In order to classify the massive historical review information of e-commerce platforms, efficiently extract review information and visualize it, this paper establishes an SVM-based e-commerce review classification model (using the combination of word frequency and information gain for feature selection), using the SVM classification model effectively classifies the review text, and uses J2EE as the developed technical framework to realize the B/S mode of the e-commerce review information system, combined with the JFreeChart plug-in to realize the visual display of review data classification, and provide conciseness for merchants and consumers Intuitive reference. This paper compares the two algorithm classification models of random forest and SVM. By comparing the results of classification experiments, it is verified that SVM can solve the small sample data classification problem in this paper more efficiently and accurately.