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


With the development of information systems, data has become one of the most important sources of organizations. Therefore, methods and techniques are need-ed to efficiently access data, share data, extract data from data, and use this infor-mation. By creating and expanding the Web and a significant increase in the vol-ume 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 tech-niques 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 con-tent 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 exam-ines 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.