Personalized Recommendation Strategy and Algorithm Optimization on Cloud Computing Platform

摘要

Information overload is a key issue of the current network information retrieval, and a personalized recommendation with special information filtering methods is an important way and means to solve this problem. Based on the analysis of the common methods used of personalized recommendation, the architectural design of the personalized recommendation is proposed on the cloud computing platform. Then, combined with the specific issues of employment recommendation, this article proposes an optimized algorithm of Mahout distributed personalized recommendation based on content and items. Compared with the current single target recommendation algorithm, this algorithm is more efficient with a good practical significance and reference value.