Micromedia News Dissemination Impact Assessment Integrated with Personalized Recommendation Algorithm | Zendy

Shaofang Guo | Zendy

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Micromedia News Dissemination Impact Assessment Integrated with Personalized Recommendation Algorithm

Author(s) -

Shaofang Guo

Publication year - 2021

Publication title -

advances in multimedia

Language(s) - English

Resource type - Journals

eISSN - 1687-5699

pISSN - 1687-5680

DOI - 10.1155/2021/5621864

Subject(s) - dissemination , computer science , collaborative filtering , recommender system , information dissemination , the internet , quality (philosophy) , world wide web , information retrieval , algorithm , telecommunications , philosophy , epistemology

The development of the Internet has completely changed the way of recommending and disseminating news content. Traditional media forms of news dissemination effectiveness evaluation methods are no longer fully suitable for the evolving needs of new media news dissemination. Therefore, it is necessary to innovate methods for evaluating the effects of new media news dissemination. This article mainly combines personalized recommendation algorithms to evaluate the effectiveness of news dissemination. Currently, popular personalized recommendation algorithms include content-based recommendation algorithms, collaborative filtering recommendation algorithms, knowledge-based recommendation algorithms, and associated recommendation algorithms. These recommendation algorithms are effective. This promotes the dissemination of news, which also recommends news content that is more relevant to user preferences for most users. In addition, the quality of news content is further evaluated through the news rating system, thereby effectively improving the quality of news content.

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