"Consumer Qoe-Aware Cognitive Semantic Sentiment Analysis Via Hybrid La" by Haiyu Xu, Zhiwei Guo et al.
 

Consumer Qoe-Aware Cognitive Semantic Sentiment Analysis Via Hybrid Large Models

Document Type

Article

Source of Publication

Ieee Consumer Electronics Magazine

Publication Date

3-1-2025

Abstract

Nowadays, the importance of Quality of Experience (QoE) has gained increasing attention from online consumers. For service providers, developing effective sentiment analysis approaches is essential to accurately capture and understand the emotional characteristics of consumers, thereby enhancing consumer QoE. However, existing research often encounters limitations in comprehending QoE and lacks fine-grained semantic analysis. To overcome these challenges, this article introduces a novel pretraining neural network structure designed for QoE-aware cognitive semantic sentiment analysis using hybrid large models. This approach utilizes a unique parallel architecture encoder that effectively captures implicit semantics within user reviews, significantly improving the model's ability to comprehend semantic sentiments. By learning diverse features, the model adeptly captures intricate word-level relationships, which enhances its generalization capabilities. Finally, the model's efficacy in sentiment analysis has been validated using real-world online consumer datasets in multilingual contexts, demonstrating its practical utility for online consumer sentiment analysis.

ISSN

2162-2248

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Volume

14

Issue

2

First Page

59

Last Page

68

Disciplines

Computer Sciences

Keywords

Sentiment analysis, Semantics, Analytical models, Encoding, Consumer electronics, Reviews, Bidirectional control

Indexed in Scopus

no

Open Access

no

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