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  • Open Access


    Automated File Labeling for Heterogeneous Files Organization Using Machine Learning

    Sagheer Abbas1, Syed Ali Raza1,2, M. A. Khan3, Muhammad Adnan Khan4,*, Atta-ur-Rahman5, Kiran Sultan6, Amir Mosavi7,8,9

    CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 3263-3278, 2023, DOI:10.32604/cmc.2023.032864

    Abstract File labeling techniques have a long history in analyzing the anthological trends in computational linguistics. The situation becomes worse in the case of files downloaded into systems from the Internet. Currently, 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 files. Currently, no significant work is done on automated file labeling during the organization of heterogeneous user files. A few attempts have been made in topic modeling. However, one major drawback of current topic modeling approaches… More >

  • Open Access


    Content Based Automated File Organization Using Machine Learning Approaches

    Syed Ali Raza1,2, Sagheer Abbas1, Taher M. Ghazal3,4, Muhammad Adnan Khan5,6, Munir Ahmad1, Hussam Al Hamadi7,*

    CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 1927-1942, 2022, DOI:10.32604/cmc.2022.029400

    Abstract In the world of big data, it's quite a task to organize different files based on their similarities. Dealing with heterogeneous data and keeping a record of every single file stored in any folder is one of the biggest problems encountered by almost every computer user. Much of file management related tasks will be solved if the files on any operating system are somehow categorized according to their similarities. Then, the browsing process can be performed quickly and easily. This research aims to design a system to automatically organize files based on their similarities in terms of content. The proposed… More >

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