Abstract
With the rapid development of Internet technology, network information is becoming more and more abundant, and people have more demands for news dissemination. However, the traditional stand-alone recommendation system cannot meet the diverse requirements of users in a short time, so the distributed recommendation algorithm is gradually evolving. At the same time, there are a lot of repetitiveness, redundancy, and low retrieval efficiency in traditional search engines. How to use these massive available resources to obtain more accurate and accurate information has become a current research hotspot. Therefore, in this case, a hybrid recommendation system came into being. The distributed hybrid recommendation algorithm provides new ideas for the development of the news dissemination innovation system. This paper adopts experimental analysis and data analysis methods, and is intended to combine distributed hybrid recommendation algorithms to explore the development of news dissemination innovation systems, so as to achieve innovations in news dissemination methods and paths. According to the experimental results, the transaction success rate was 99%, 99%, 98%, 96%, and 93%. It can be seen that the transaction success rate of the system is relatively high. When the number of visitors is less than 200, the transaction success rate is close to 100%, which can better meet the needs of users.
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Liu, Y. (2022). Distributed Hybrid Recommendation Algorithm in News Dissemination Innovation System. In: Sugumaran, V., Sreedevi, A.G., Xu, Z. (eds) Application of Intelligent Systems in Multi-modal Information Analytics. ICMMIA 2022. Lecture Notes on Data Engineering and Communications Technologies, vol 136. Springer, Cham. https://doi.org/10.1007/978-3-031-05237-8_3
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DOI: https://doi.org/10.1007/978-3-031-05237-8_3
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