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With the rapid development of information technology and the rapid growth of data, the era of big data has come. Rational use of big data technology to improve the contribution quality of network teaching resources, to achieve comprehensive sharing of teaching resources, will be the trend of future development. The rapid development of big data technology has created good opportunities for improving the network informatization level of party construction in colleges and universities. In the era of big data, the innovation of party construction in colleges and universities has its necessity and possibility. However, traditional resource-sharing technology can not accurately identify heterogeneous resources, resulting in a poor sharing effect. Therefore, based on big data analysis, this paper studies the sharing technology of educational resources for party history study of party members in colleges and universities. By constructing a resource-sharing model, semantic recognition of heterogeneous educational resources is carried out, and semantic relations between concepts are obtained by reasoning. Based on similar semantics, big data analysis algorithm is used to calculate semantic similarity, and other resources associated with the resource are retrieved according to semantic similarity to realize resource-sharing. In the experimental demonstration, the semantic similarity between different concepts is calculated by the design method and the traditional method respectively. Experimental results show that the semantic similarity calculated by the resource-sharing technology based on big data analysis is closer to the expected value. The semantic similarity can also better identify heterogeneous resources and achieve a better sharing effect. The learning education resource-sharing technology based on a big data analysis algorithm is feasible, which can lay a foundation for resource-sharing technology and help users rationally use more educational resources.
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