The Study And Implementation Of The Author’s Recommendation System

With the rapid development of network technology,mankind has entered the new era of informatization.In this era of informationization,on the one hand,human beings are providing more and more information and services on the Internet.On the other hand,it’s hard for humans to find information that suits their appetites.To solve the problem of finding information,the search engine emerges as a passive way to provide convenience to humans,but it doesn’t solve the problem completely.,recommendation systems appear in our life,it has changed the original search engine service,provide service for the user,in the form of active users looking for information has become easier.With the theme of recommendations found in China know network platform for retrieval,recommender system has been widely used in various aspects of life,the most widely used in the field of electricity,while relatively few applications in the field of publishing.With the development of information technology,the authors in the field of digital publishing source is more and more diversified,published within the territory in order to solve the difficulty of editors’ choice from the media,the author in this paper,the publication,the authors recommend system research and implementation of the subject.This paper has developed a complete recommendation system.The whole system can be divided into five modules: data acquisition,data processing,data storage,user information acquisition,and recommendation.The data acquisition module is implemented by python programming,which is responsible for obtaining information from WeChat platform and obtaining the information of information acquisition based on thematic information.Data processing module through the LAMP(Linux + Apache + PHP + Mysql)architecture programming implementation,responsible for the processing of data source,data source based on keyword extraction algorithm is labeled,processing,get the number from the media,the public’s profession;The recommendation module is the core module of the whole system,and it is realized through LAMP architecture,which is based on improved collaborative filtering recommendation algorithm.The whole system has been tentatively applied to a publishing house,which brings convenience to the editors and provides reference value for the publisher to choose the appropriate self-media author.