Abstract:One of the bases for judging the competitive and cooperative relationship of enterprises is patent. In the context of big data era, the number of patents has soared, and the prediction of potential relationship between enterprises should not only use reasonable methods to narrow the search scope, but also combine the concept of time series to make hierarchical recommendation. Taking perovskite solar cells as an example, based on word2vec word vector model and LDA model, data mining and corpus expansion of patent text were carried out. Based on the theory of technology life cycle, collaborative filtering recommendation algorithm was used to predict the competition and cooperation relationship between enterprises, and a gradient coefficient was constructed to judge the competition and cooperation intensity. The research results show that in the field of perovskite-type solar cells, the idea of collaborative filtering based on the time dimension is applicable to the judgment of potential relationships between enterprises, and the prediction results of the algorithm have also passed the empirical test; At the same time, based on the patent perspective, the competition and cooperation between enterprises can be divided into potential strong cooperation, potential weak cooperation, potential strong competition and potential weak competition and cooperation. Research and clarify the potential competition and cooperation relationship between enterprises, and provide new methods for enterprises to retrieve potential relationship objects in the future.