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Analysis of Product Selection Strategy for Cross-Border E-Commerce with Assistance of Artificial Intelligence

Lin Feng,

Abstract


The expansion of the e-commerce sector beyond international boundaries has opened up new opportunities in international business. The first and most important problem for international e-commerce businesses is choosing the right products to sell. Scientific product selection is important not only for the smooth running of international e-commerce businesses, but also for the growth and development of thriving private labels. With development for Internet and rapid rise of e-commerce platforms, online shopping has become mainstream. While consumers are deeply involved, a large number of user comments appear on the Internet, and these online shopping comments often contain a lot of valuable information. Cross-border e-commerce can get useful suggestions and feedback about products through sentiment analysis of these texts. This can also find product problems, improve where they are not in place, and improve operational efficiency. This work studies the selection strategy of cross-border e-commerce products assisted by artificial intelligence technology. This paper uses artificial intelligence technology to conduct sentiment analysis of product reviews, which can help cross-border e-commerce companies make effective product selection. This work proposes CNN-BiGRU-ATT for sentiment polarity analysis of product reviews. First, the multi-channel convolutional neural network is utilized to extract local feature of different granularities. Then connect BiGRU for context sequence learning to memorize long-distance dependency information. This method not only solves the problem that CNN cannot perform context sequence learning, but also solves issue of gradient disappearance or explosion. Finally, attention is introduced after the BiGRU hidden layer to filter the important features.

Keywords


Product selection, Cross-border E-commerce, AI, CNN-BiGRU-ATT

Citation Format:
Lin Feng, "Analysis of Product Selection Strategy for Cross-Border E-Commerce with Assistance of Artificial Intelligence," Journal of Internet Technology, vol. 26, no. 1 , pp. 111-121, Jan. 2025.

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Published by Executive Committee, Taiwan Academic Network, Ministry of Education, Taipei, Taiwan, R.O.C
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