Automated File Labeling for Heterogeneous Files Organization Using Machine Learning

作     者：Sagheer Abbas Syed Ali Raza MAKhan Muhammad Adnan Khan Atta-ur-Rahman Kiran Sultan Amir Mosavi 

作者机构：School of Computer ScienceNational College of Business Administration&EconomicsLahore54000Pakistan Department of Computer ScienceGC University LahorePakistan Riphah School of Computing&InnovationFaculty of ComputingRiphah International UniversityLahore CampusLahore54000Pakistan Department of SoftwarePattern Recognition and Machine Learning LabGachon UniversitySeongnam13120Korea Department of Computer ScienceCollege of Computer Science and Information Technology(CCSIT)Imam Abdulrahman Bin Faisal University(IAU)P.O.Box 1982Dammam31441Saudi Arabia Department of CITThe Applied CollegeKing Abdulaziz UniversityJeddah31261Saudi Arabia John von Neumann Faculty of InformaticsObuda UniversityBudapest1034Hungary Institute of Information EngineeringAutomation and MathematicsSlovak University of Technology in BratislavaBratislava81107Slovakia Faculty of Civil EngineeringTU-DresdenDresden01062Germany 

出 版 物：《Computers, Materials & Continua》 (计算机、材料和连续体（英文）)

年 卷 期：2023年第74卷第2期

页      面：3263-3278页

核心收录：

学科分类：12[管理学] 1201[管理学-管理科学与工程(可授管理学、工学学位)] 081104[工学-模式识别与智能系统] 08[工学] 0835[工学-软件工程] 0811[工学-控制科学与工程] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

主　　题：Automated file labeling file organization machine learning topic modeling 

摘      要：File labeling techniques have a long history in analyzing the anthological trends in computational *** situation becomes worse in the case of files downloaded into systems from the ***,most users either have to change file names manually or leave a meaningless name of the files,which increases the time to search required files and results in redundancy and duplications of user ***,no significant work is done on automated file labeling during the organization of heterogeneous user files.A few attempts have been made in topic ***,one major drawback of current topic modeling approaches is better *** rely on specific language types and domain similarity of the *** this research,machine learning approaches have been employed to analyze and extract the information from heterogeneous corpus.A different file labeling technique has also been used to get the meaningful and`cohesive topic of the *** results show that the proposed methodology can generate relevant and context-sensitive names for heterogeneous data files and provide additional insight into automated file labeling in operating systems.