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Big Data Aspect-Based Opinion Mining Using the SLDA and HME-LDA Models
2020
Wireless Communications and Mobile Computing
In order to make better use of massive network comment data for decision-making support of customers and merchants in the big data era, this paper proposes two unsupervised optimized LDA (Latent Dirichlet Allocation) models, namely, SLDA (SentiWordNet WordNet-Latent Dirichlet Allocation) and HME-LDA (Hierarchical Clustering MaxEnt-Latent Dirichlet Allocation), for aspect-based opinion mining. One scheme of each of two optimized models, which both use seed words as topic words and construct the
doi:10.1155/2020/8869385
fatcat:6e72klhmtvh2fmewjwmucoaq5y