Recommendation Research of Science and scientific and technological reports for the Needs of Science and Technology Enterprises

¹ School of Economics, Wuhan University of Technology, 430070, China
² Hubei Provincial research Center for E-Business Big Data Engineering Technology, 430070, China

Abstract

To improve the scientific research and innovation ability of science and technology enterprises, we recommend science and technology reports for the individual demandss of science and technology enterprises, and provide scientific theory and technical support. This paper proposes a technology report recommendation method that integrates feature value and time value for the demandss of science and technology enterprises. Firstly, the TF-IDF algorithm and word2vec language model are used to construct the feature vector of technology enterprise demand. Secondly, LDA, TF-IDF and word2vec are used to construct the feature vector of scientific and technological reports, and the time value of scientific and technological reports is calculated by referring to the negative exponential equation of literature aging and the half-life index of downloads. Finally, the similarity is calculated between the technology enterprise demand feature vector and the technology report vector, and the final recommendation results are obtained by sorting and comparing with other methods. The empirical results show that the scientific and technological reports recommended by this paper’s methodology not only meet the demandss of science and technology enterprises, but are also novel and cutting-edge.