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Linkages between science and technology have been extensively studied using nonpatent literature citations or author-inventor matching. These methods suffer from limitations, such as the lack of citations to relevant documents or challenges with the disambiguation of author–inventor linkages. To mitigate these limitations, this paper uses Latent Dirichlet Allocation to create topic-based linkages between publications and patents based on the semantic content in the documents. The approach allows for the detection of topical overlap between patent and scientific publications, highlighting topical areas shared by research and application. Using a case study on “Taxol,” a cancer drug, with in total 26 475 documents retrieved from EuropePMC database the study illustrates the performance of the approach. The study offers qualitative and quantitative support that the approach is valuable in detecting patent and publication linkages. [ABSTRACT FROM AUTHOR]