Extracting product competitiveness through user-generated content: A hybrid probabilistic inference model

Extracting product competitiveness through user-generated content: A hybrid probabilistic inference model

A BERT-MDLP-Bayesian Network model (BMB) is proposed to analyze the improvement strategy of e-commerce products based on user generated content (UGC). The proposed model can be represented into four parts: clearing redundant data on the obtained UGC, extracting product attributes and word vector to...

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Bibliografische gegevens
Hoofdauteurs: Ming-Fang Li, Guo-Xiang Zhang, Lu-Tao Zhao, Tao Song
Formaat: Artikel
Taal:English
Gepubliceerd in: Elsevier 2022-06-01
Reeks:Journal of King Saud University: Computer and Information Sciences
Onderwerpen:
Text mining
Bayesian network
Social media
Sentiment analysis
User-generated content
Online toegang:http://www.sciencedirect.com/science/article/pii/S1319157822001021

Internet

http://www.sciencedirect.com/science/article/pii/S1319157822001021

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