Improving Diversity with Multi-Loss Adversarial Training in Personalized News Recommendation

Ruijin Xue; Shuang Feng; Yanyan Wang

doi:10.32604/cmc.2024.052600

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JOURNAL ARTICLE

Improving Diversity with Multi-Loss Adversarial Training in Personalized News Recommendation

Ruijin Xue Shuang Feng Yanyan Wang

Year: 2024 Journal: Computers, materials & continua/Computers, materials & continua (Print) Vol: 80 (2)Pages: 3107-3122

DOI: 10.32604/cmc.2024.052600

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Keywords:

Adversarial system Training (meteorology) Diversity (politics) Computer science Multimedia World Wide Web Artificial intelligence Information retrieval Political science Geography

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Computational and Text Analysis Methods

Social Sciences → Social Sciences → General Social Sciences

Text and Document Classification Technologies

Physical Sciences → Computer Science → Artificial Intelligence

Sentiment Analysis and Opinion Mining

Physical Sciences → Computer Science → Artificial Intelligence

Improving Diversity with Multi-Loss Adversarial Training in Personalized News Recommendation

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Citation History

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