When using the current method to update the index of educational resources, there is no analysis of the hierarchical association structure between educational resources. There are some problems such as too long index construction time, high query time and low query accuracy. Therefore, this paper introduces mobile computing to study the adaptive updating method of education resource index. This paper analyzes the structure of the index system of educational resources. On the basis of mobile computing, the hierarchical association structure between educational resources is analyzed by LDA (Latent Dirichlet Allocation) topic modeling and topic hierarchical clustering. The initial query is expanded by selecting extension words by local co-occurrence method. The weight of the extended query is allocated by genetic algorithm to realize the adaptive updating of the index of educational resources. The experimental results show that when the number of nodes is 25 × 104, the total query time of this method is only 3.5 s, and the average index redundancy rate is only 0.22%, indicating that the resource index update performance of this method is better. © 2021, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.