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  • Open Access

    ARTICLE

    ABMRF: An Ensemble Model for Author Profiling Based on Stylistic Features Using Roman Urdu

    Aiman1, Muhammad Arshad1, Bilal Khan1, Khalil Khan2, Ali Mustafa Qamar3,*, Rehan Ullah Khan4

    Intelligent Automation & Soft Computing, Vol.39, No.2, pp. 301-317, 2024, DOI:10.32604/iasc.2024.045402

    Abstract This study explores the area of Author Profiling (AP) and its importance in several industries, including forensics, security, marketing, and education. A key component of AP is the extraction of useful information from text, with an emphasis on the writers’ ages and genders. To improve the accuracy of AP tasks, the study develops an ensemble model dubbed ABMRF that combines AdaBoostM1 (ABM1) and Random Forest (RF). The work uses an extensive technique that involves text message dataset pretreatment, model training, and assessment. To evaluate the effectiveness of several machine learning (ML) algorithms in classifying age and gender, including Composite Hypercube… More >

  • Open Access

    ARTICLE

    Predicting Age and Gender in Author Profiling: A Multi-Feature Exploration

    Aiman1, Muhammad Arshad1,*, Bilal Khan1, Sadique Ahmad2,*, Muhammad Asim2,3

    CMC-Computers, Materials & Continua, Vol.79, No.2, pp. 3333-3353, 2024, DOI:10.32604/cmc.2024.049254

    Abstract Author Profiling (AP) is a subsection of digital forensics that focuses on the detection of the author’s personal information, such as age, gender, occupation, and education, based on various linguistic features, e.g., stylistic, semantic, and syntactic. The importance of AP lies in various fields, including forensics, security, medicine, and marketing. In previous studies, many works have been done using different languages, e.g., English, Arabic, French, etc. However, the research on Roman Urdu is not up to the mark. Hence, this study focuses on detecting the author’s age and gender based on Roman Urdu text messages. The dataset used in this… More >

  • Open Access

    ARTICLE

    Author’s Age and Gender Prediction on Hotel Review Using Machine Learning Techniques

    Muhammad Hood Khan1, Bilal Khan1,*, Saifullah Jan1, Muhammad Imran Chughtai2

    Journal on Big Data, Vol.5, pp. 41-56, 2023, DOI:10.32604/jbd.2022.044060

    Abstract Author’s Profile (AP) may only be displayed as an article, similar to text collection of material, and must differentiate between gender, age, education, occupation, local language, and relative personality traits. In several information-related fields, including security, forensics, and marketing, and medicine, AP prediction is a significant issue. For instance, it is important to comprehend who wrote the harassing communication. In essence, from a marketing perspective, businesses will get to know one another through examining items and websites on the internet. Accordingly, they will direct their efforts towards a certain gender or age restriction based on the kind of individuals who… More >

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