Research on Labeling System for Radio and Television Intelligent Recommendation System
Authors: 
Yuanjia Gong, Chong ZhangAuthors Info & Claims
Yuanjia Gong, Chong ZhangAuthors Info & ClaimsPages 599 - 603
Abstract
The purpose of this paper is to study the labeling system for radio and television intelligent recommendation system. By analyzing user behavior data, user profile data, TV portrait data and scenario-based data, a multi-dimensional user interest model is constructed. Using natural language processing and machine learning technology, it automatically extracts and summarizes labels from program introductions, user comments, and behavior logs, and continuously optimizes and updates the labeling system through a continuous user feedback loop. At the same time, a credible weighted labeling system is designed to improve the accuracy of the recommendation system and the personalized experience of users.
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- Research on Labeling System for Radio and Television Intelligent Recommendation System
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Published In
June 2024
1206 pages
ISBN:9798400710247
DOI:10.1145/3690407
Copyright © 2024 Copyright held by the owner/author(s). Publication rights licensed to ACM.
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Association for Computing Machinery
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Published: 24 October 2024
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CAIBDA 2024
CAIBDA 2024: 2024 4th International Conference on Artificial Intelligence, Big Data and Algorithms
June 21 - 23, 2024
Zhengzhou, China
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