Design And Implementation Of Book Share Platform Based On Association Rules

Nowadays,Internet technology has become increasingly mature.More and more people enjoy digital conveniences.The latest research data shows that the number of China's Internet users has reached 751 million.The vast majority of Internet users are willing to share daily life,comment and so on.The neglected sharing of information,if exploited properly,will bring great potential value.The books which are the crystallization of human wisdom have always been the most important partner in people's production and life.ln the age of big data,it is becoming more difficult for readers to search for the most suitable books from the vast resources.This paper takes into account the practical issues and combines the advantages of sharing mode using data mining method of association rules to analyze book records and review information shared by readers.The purpose is to build a personalized book recommendation and sharing platform.In data mining,Association rules are an important branch,by analyzing dependencies between different itemsets,we find more interesting itemsets association.After studying the advantages and disadvantages of traditional Apriori algorithm and combining the habit of reading and sharing,an improved weighted association rule algorithm is proposed in this paper.In addition,the initial data set comes from the doban.com,using the API interface provided by the website to capture all records related to both users and books.Among them,the book mark and book review information are weight calculation and the weight calculation is added to the support calculation method,so the frequent itemsets and association rules are obtained.Moreover,considering the stage of book reading and heat promotion,we will segment the relevant information of the books recorded in the database according to a certain time sequence,and strong correlation generated in each round will be entered into the subsequent mining analysis.Finally,the improved algorithm is applied to the development of the book sharing software platform.The main contents of the article are as follows:(1)Summarize current development of association rule mining algorithm,web crawler technology and sharing mode.(2)Describe the details of improved weighted association rule algorithm based on traditional Apriori algorithm.(3)Introduce design and implementation process of the book sharing platform,and this software is implemented in strict accordance with the development process.(4)According to the experimental data and software test results,test and analyze the algorithm and platform environment.By analyzing the data of books shared by users,we can deduce the potential association between different books to provide users with more personalized services.Platform provides higher quality service function,can enhance customer loyalty and satisfaction,so that there are more sharing data and data mining results will be more accurate to form a virtuous circle.The innovations of this paper are as follows:(1)Introduce the concept of weight to increase the weight rules associated with books,so that data mining results are more suitable to reality.(2)Increasing the processing of sequential time,the relation data of books is segmented and processed to reduce the number of operations of the whole data,and to improve of book association rules.