Product Personailzed Recommendation Method And Implements Based On Innovation And Entrepreneurship Competition

With the advent of the era of big data and the continuous development of data mining technology,the way to deepen the application of big data technology in innovation and entrepreneurship education has become the focus of attention.College students’ innovation and entrepreneurship competitions,as an important method to cultivate innovative and entrepreneurial talents,have been highly valued by the state and actively cooperated by universities.In the management of innovation and entrepreneurship events,teachers and students in universities also put forward the continuous improvement and optimization of the information management system,and used data mining technology to provide new demands for personalized and targeted services.At the same time,in the innovation and entrepreneurship event management system of most universities,search engine technology is still used to provide information retrieval function for users,but this technology is only applicable to search under the condition of clear needs.Under the background of the accumulation of information information in the management system year by year and the lack of practical experience of teachers and students,the further development of the innovation and entrepreneurship event management system is restricted.Therefore,this paper applies personalized recommendation technology to entrepreneurship and innovation events.Taking this as the research object,it combines complex network tags with traditional content-based recommendation methods to build a personalized recommendation system for mass entrepreneurship events,so as to provide users with convenient,reliable and efficient information recommendation services related to mass entrepreneurship events.First,this paper introduces the research background and purpose of personalized recommendation method for entrepreneurship and innovation events,and expounds the development status and existing problems of the system.According to the characteristics of large amount of text information in the mass entrepreneurship and innovation event system,the tag is used as a resource classification method in the construction of the system,and the semantic based Text Rank text keyword extraction algorithm is proposed to obtain text keywords as the initial label of resources.In order to solve the problem that the polysemy of words may lead to ambiguous label semantics,the concept of complex network was introduced,and the complex tag network was constructed.Clustering analysis was carried out on the complex tag network to generate different tag clusters,which were used as units to classify resources.Then,aiming to solve the problems of user interest variation and matrix sparsity in the recommendation of mass entrepreneurship and innovation events,a content recommendation method based on complex label network was constructed by combining user portrait and contentbased recommendation method.Time weight is introduced in the construction of user portrait,and the change of user interest and preference is simulated by the way of time and frequency weight,so as to recommend more accurate resource information for users.By using the technology of extracting text keywords as the initial label of text resources in the system,the problem of cold start of recommendation algorithm is solved.By using labels as a classification method of resources,the problem of low recommendation efficiency caused by sparse matrix data is alleviated to a certain extent.By comparing the proposed recommendation method with the mainstream recommendation algorithm,the superiority of the proposed recommendation algorithm is verified through the design experiment.Finally,to design a personalized recommendation system for entrepreneurship and innovation events,and describe the requirements and construction scheme of the system in detail.The recommendation system is divided into system management module,data acquisition and storage module,recommendation engine module.The recommendation engine module is the core of the personalized recommendation system,and its implementation mechanism is described in detail.In this paper,the appropriate personalized recommendation method is applied to the event system of mass entrepreneurship and innovation,so that the event management system has the ability of "thousands of people and thousands of faces".It is of great significance to stimulate the innovation and entrepreneurship potential of college students,increase the communication channels between teachers and students,and stimulate the enthusiasm of teachers and students to participate.