The Research Of Recommended Algorithm In Scientific Research Achievement Management System

Converting scientific and technological achievements in universities into a driving force for science and technology and economic development,and promoting economic and social development are of great significance in enhancing the ability of scientific and technological innovation and promotion,enhancing the independent innovation capability of agricultural science and technology,and consolidating and improving comprehensive agricultural production capacity.However,the results of scientific research in universities are hard to be discovered and applied by enterprises and it is difficult for companies to find breakthroughs through certain achievements and innovative technologies.Therefore,it is particularly important to research and establish scientific research achievement systems in universities.On the one hand,it provides conditions of practical value for the results of technology in colleges and universities,and on the other hand,it promotes the speed of development of enterprises and provides a powerful guarantee for the transformation of scientific research achievements in universities into practical productivity.When enterprise users search for university patent achievements,their needs are often vague and general.In order to meet the user’s search requirements,it is necessary for us to carry out the research and discussion of the recommendation function in the scientific research achievement system in universities so that these outcome technologies can be more easily and accurately delivered to the people in need,so as to improve the efficiency of the transformation of scientific research results.The application of the research recommendation algorithm in the scientific research achievement system of universities has strengthened the intelligent push of scientific research projects,improved the efficiency of scientific research work,and enhanced the conversion rate of scientific research achievements in information.On the basis of TF-IDF recommendation algorithm,this paper proposes the method of setting feature weight.Research on word segmentation and word frequency calculation of patent terms based on NIPIR word segmentation system,through the analysis of the user’s search behavior,using the TF-IDF text recommendation algorithm to establish a user preference database,according to the preference ordering,the information that satisfies the user’s fuzzy requirements is actively pushed to the user from a large amount of user search information,which helps to translate potential requirements into actual needs and helps improve the efficiency of transformation of scientific research achievements in universities,realizes the friendly docking between scientific research institutions and application organizations.At the same time,it will also improve the ability of scientific and technological innovation and promotion.By constructing a user interest model and a recommendation algorithm which be integrated,improving the intelligent search efficiency,enhancing the accuracy of the scientific research management system.At the same time,constructing a database and designing a university scientific research management query system,and test to ensure the quality of the system.