The Design And Implementation Of Digital Ancient Books Library Based On SSM

As the product and support of Chinese history and culture,ancient books are also the crystallization of ancient Chinese civilization,with important academic significance and historical relic value.Most of the ancient books are preserved on paper,which is not convenient for searching and borrowing.In recent years,with the rapid development of internet technology,people's requirements for accessing information resources have increased.Especially in the case of network sharing,people hope that resources can be shared in the form of networks without being limited by time and space.Such an open access method can meet the needs of users to a certain extent,and it can solve the problem that the ancient books are difficult to find,difficult to borrow,and difficult to read.Network technology and computer technology are combined to research and design a digital ancient book library system based on SSM framework with personalized recommendation algorithm.Firstly,this paper analyzes the research status of digitization work of ancient books at home and abroad,and clarifies the research tasks and research significance of this paper.The main problems and challenges of the research is etrieval problems of the massive data,the storage problem of massive image,and the personality recommendation algorithm to the digital ancient books library.Combined with the requirements of the digital ancient book library system,the system is analyzed,and the system is divided into five major functional modules: system management module,retrieval module,online reading module,personal center module and personalized recommendation module.Next,the book personalized recommendation algorithm based on user behavior and user attribute clustering are studied,and the paper proposes the improvement of the model and the improvement of the algorithm.Combined with the user behavior log of an e-book website,the user average reading time model and reading frequency model are proposed,and the final scoring model is established based on the user's display score and collection behavior.The appropriate weights are selected through multiple sets of experimental comparisons.Then an improved FunkSVD algorithm with sentiment enhanced is proposed to predict the user's score on the book.The algorithm can resolve the difference between user ratings well.Finally,the personalized recommendation algorithm is experimentally evaluated and verified.The basic recommendation algorithm and collaborative filtering algorithm are compared to prove that the algorithm has good recommendation effect.The personalized recommendation algorithm based on user behavior has a cold start problem.Then,the cluster recommendation algorithm based on user attributes are improved,selects users with high activity as the initial cluster center,and uses K-means clustering algorithm to recommend books for new users.Experiments verify that it can solve the user's cold start problem well.Finally,the digital ancient book library system is designed and implemented in detail.The system uses SSM as the basic framework,uses ElasticSearch full-text search engine to solve the problem of massive ancient books data retrieval,uses FastDFS distributed file system to solve the problem of massive image storage,and adopts personalized recommendation algorithm based on user behavior and user attribute clustering to recommend books for users..In addition,the system also implements the user rating function,the user collection function,and the user browsing record query function.At the same time,AngularJS,HTML,CSS and other open source technologies are used to design the front-end interface,which makes the system have a good user experience.What's more,the various modules and application servers are deployed which the system depends on.According to its operation in the server,it verifies that the system has strong scalability and good user interaction.