Research And Application On Recommending University For Industry-University Cooperation

In the background of Public Entrepreneurship,Innovation,the deployment and implementation of innovation-driven development strategy is one of the priorities of our government.On the road of improving the capability of independent innovation,Industry-University cooperation plays an irreplaceable role in guiding and supporting the integration of innovation elements into enterprises and universities and promoting the transformation of scientific and technological achievements into productive forces.With the continuous advancement of Industry-University cooperation,many problems have been discovered:The depth of cooperation needs to be deepened;Scientific and technological achievements of universities can not be effectively connected with the real needs of the market and it will affect the quality.Due to the lack of appropriate channels and information access platform,it's likely to cause information asymmetry between the enterprise and universities.In general,enterprises,as the demand-side,choose to cooperate with universities in a single way,which is mostly through school fame or acquaintance introduction,it will lead to the university's related capbility can not match with the demand of the enterprise,which makes the university which is not famous but has strong professional capbility in the related field lose cooperation opportunities,and corporation resources can not be reasonably configured.With the development of the Internet,the problem of information overload makes the information filtering become very important.How to make use of the advanced big data technology,to solve the current information asymmetry problem between enterprises and universities through the analysis of the massive data,and choose the right Industry-University cooperation partner,so as to achieve a more rational allocation of resources,improve the quality and efficiency of the cooperation.It will become the focus of this paper.This paper is about Industry-University cooperation.Through analyzing the current situation and studying the related literature,this paper summarized the key indicators of cooperation capbility of universities,which lays the foundation for the construction of recommendation model.From the enterprises' needs,it makes text preprocessing,feature extraction and keyword classification for the demand content and then needs can be more accurately assigned to a particular area or category.From the view of the enterprises to choose partners,based on the characteristics of Industry-University cooperation and the three key indicators,such as the basic scientific research capbility of universities,the transformation capbility of universities and the background of university in Industry-University Cooperation,this paper continues to refine and enrich indicators.Combined with expert advice,this paper uses 5 scale calibration method,through the least square method to make regression fine-tuning,and finally determines the weight of the indicators at all levels.Based on the enterprise demand category information,this paper uses related technology in web crawler by adding in asynchttpclient package and htmlparser package,to get a part of information of universities which is matched the category,including papers and research projects.And then builds a recommendation algorithm model based on enterprise demand,validates the algorithm through an example.Finally,this paper uses object-oriented method,analyzing,modeling and designing the recommendation system based on UML.The interface of the system is designed with Axure RP prototyping tool.The display and interaction of the Web page are completed.The recommendation model is further applied.