An Effective Algorithm to Improve the Accuracy of Recommender System based on Comments using Classification Techniques in Data Mining

Abstract

With the development of information systems, data has become one of the most important sources of organizations. Therefore, methods and techniques are needed to efficiently access data, share data, extract data from data, and use this information. By creating and expanding the Web and a significant increase in the volume of information and web development, the need for methods and techniques that can provide data efficiently and extract information from them is felt more than ever. Web mining is one of the areas of research that uses data mining techniques to automatically discover information from web services and documents. In fact, Web mining is a process of discovery of unknown and useful information from web data. Web mining methods are categorized into three types of web content exploration, exploration of Web structures, and exploration of the use of the Web, based on what type of data they are exploring. This research investigates the relationship between the idea of mining and other research fields and examines some of the previous methods used. Finally, a method is proposed based on two decision tree and machine model algorithms that will improve the results of the idea of mining. The results of the simulation of the proposed method were evaluated and compared with the previous methods. The results show that the proposed method has higher accuracy and speed