Big Data Algorithm and Zhejiang Opera Culture Gene Mapping

This paper proposes the design of the Zhejiang opera culture gene map using the Zhejiang opera culture gene and gene map. Secondly, it focuses on the application of data mining algorithms in managing opera culture resources, including indexing and querying of dissemination track data and mining Zhejiang opera culture data resources. Finally, the application effect of data mining in Zhejiang opera culture gene mapping is demonstrated through an example analysis. The results show that for the multi-valued attribute dataset of trajectory data of Zhejiang opera culture, the execution time of the optimized algorithm is reduced by 848 ms under a 1% support rate and 88 ms under a 10% support rate compared with the Apriori algorithm. This paper reveals the inner connections and characteristics of Zhejiang opera culture through a data mining algorithm for cultural gene mapping, providing a scientific basis.