Research on User Enhanced Experience for Public Digital Cultural Services

On the basis of analyzing the needs of modern public digital culture and maximizing the value of personalized information, it is oriented to the "National Library Open Course" platform and resolves user intention mining from the two directions of analyzing user portraits and resource data. This paper proposes a personalized information recommendation service model oriented to "National Library Open Course ", and gives a solution to the personalized service recommendation system based on user behavior characteristics, which can effectively solve the problem of unsatisfactory recommendation performance caused by sparse matrix data. Experiments were conducted on the "National Library Open Course" of the National Library, and the comparative experiment achieved good results. The research results obtained effectively improved the user experience and cultural resource utilization efficiency of the National Library Open Course.