基于模糊聚类的博物馆藏品推荐算法研究

ue to the complexity and variety of museum collections, it takes time and energy for visitors to visit. This paper will introduce the recommended algorithm into the intelligent construction of the museum to effectively alleviate this problem. In the recommendation system, the fuzzy clustering algorithm is used to cluster the data to accelerate the convergence speed of the algorithm. The fuzzy clustering algorithm has good anti-noise performance, but it has the disadvantage of being easily trapped in local optimum. the Fuzzy C-Means algorithm is used to improve the fuzzy clustering algorithm by optimizing the initial clustering in this paper. Experimental results show that the optimized algorithm improves the efficiency and accuracy of the recommendation system.