Research on User Profile Construction Method Based on Improved TF-IDF Algorithm

作     者：SHAO Ze-ming LI Yu-ang YANG Ke WANG Guo-peng LIU Xing-guo CHEN Han-ning SI Zhan-jun 邵泽明;李宇昂;杨可;王国鹏;刘兴国;陈瀚宁;司占军

作者机构：College of Artificial IntelligenceTianjin University of Science and TechnologyTianjin 300457China The Open University of ChinaBeijing 100039China Engineering Research Center of Integration and Application of Digital Learning TechnologyMinistry of EducationBeijing 100039China 

出 版 物：《印刷与数字媒体技术研究》 (Printing and Digital Media Technology Study)

年 卷 期：2024年第6期

页      面：110-116页

学科分类：081203[工学-计算机应用技术] 08[工学] 0835[工学-软件工程] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

主　　题：TF-IDF-K algorithm User profiling Equalization factor SVM 

摘      要：In the data-driven era of the internet and business environments,constructing accurate user profiles is paramount for personalized user understanding and *** traditional TF-IDF algorithm has some limitations when evaluating the impact of words on classification ***,an improved TF-IDF-K algorithm was introduced in this study,which included an equalization factor,aimed at constructing user profiles by processing and analyzing user search *** the training and prediction capabilities of a Support Vector Machine(SVM),it enabled the prediction of user demographic *** experimental results demonstrated that the TF-IDF-K algorithm has achieved a significant improvement in classification accuracy and reliability.