Intelligent information recommendation algorithm under background of big data land cultivation

摘要

In order to solve the problem of serious information overload in the era of big data and improve the informatization of intelligent recommendation result, an intelligent information recommendation algorithm based on user preference mining was put forward. According to the background of big data, user behavior data is unified. The advantage of spark relative to compared Hadoop Map Reduce was analyzed through the operating architecture and upper ecosystem of spark, so that the data processing ability was improved. The user preference mining technology was integrated with the intelligent information recommendation algorithm. Moreover, the explicit user preference knowledge and implicit user preference knowledge were analyzed to obtain the user preference knowledge and the nearest neighbor community, and thus to complete the intelligent information recommendation. Experimental results show that the proposed algorithm can exactly reflect the user preferences in different groups, with good recommendation accuracy. In addition, the desired effect is achieved.