As educational resources continue to accumulate, the amount of data in ideological and political resource databases has increased exponentially. However, due to disparities in data formats and metadata standards among various databases, cross-database retrieval has emerged as a significant challenge. To tackle this issue, this article introduces an innovative cross-database retrieval strategy that leverages multi-source information fusion technology. By conducting thorough research on the data characteristics of ideological and political resources and utilizing information-level fusion techniques, we have achieved resource integration and standardization across different databases, resulting in a unified resource database that simplifies the retrieval process and enhances accuracy. Furthermore, we have designed comprehensive cross-database retrieval processes that encompass database structure integration, retrieval model construction, and practical applications. The experimental results show that the cross database retrieval method based on multi-source information fusion in this paper is significantly better in retrieval efficiency and performance than traditional single database retrieval methods, especially suitable for complex and diverse course ideological and political resource retrieval, improving the accuracy and recall of retrieval.