Research On Personal Books Recommendation System Based On Association Rule Visualization Technology

The purpose of this article is to make the personal books recommendation systemoperate normally by association rule visualization technology, Which uses rational booksrecommendation algorithm which is called Apriori algorithm and provides readers withclear and easy to understand interface to reduce readers’ borrowing time. It providesquality service according to readers’ individual demand, which increases the utilization oflibrary resources. It uses Literature analysis, model analysis and empirical analysis methodconsidering the characters of object. We mainly researched from the following aspects.Firstly, on the basis of introducing the background and significance of this research, Ianalyze the present situation of theoretical in the personal recommendation system, datamining visualization technology and recommendation system based on data miningvisualization technology, and also expound the basic knowledge of personalrecommendation and visualization technology, which lays the theoretical foundation ofthis article.Secondly, this article analyzes the demand for personal recommendation system anddiscusses the phenomenon that basic recommendation way of information retrieval cannotmeet readers’ borrowing demand and also the search results are stereotyped and lack ofpersonality. It analyses and compares the existing recommendation technology andproposes association rule applied in the library.Thirdly, According to the character of service targets, it puts forward visualizationtechnology combining with association rule recommendation technology and proposesDiamond-base Association Rule Visualization Model (DARVM) on the basis of analyzingthe corrupt practices of basic association rule visualization models applied in booksrecommendation which wastes resources of screen and accommodates less information.The model which makes information accommodated on the spatial location through spatialcognition and distributes screen resources according to level of parameters probability canmake readers manage recommendation information overall, find favorite knowledge andreceive quality service. Finally, books recommendation system is built based on DARVM. It mines readers’borrowing pattern from readers database using Apriori algorithm and shows books usingclear model which provides basis for readers who borrow books and supply readers’demand.