Výsledky vyhledávání

Report

Empirical and Experimental Insights into Data Mining Techniques for Crime Prediction: A Comprehensive Survey

Autor: Taha, Kamal

This survey paper presents a comprehensive analysis of crime prediction methodologies, exploring the various techniques and technologies utilized in this area. The paper covers the statistical methods, machine learning algorithms, and deep learning t

Externí odkaz: http://arxiv.org/abs/2403.00780

Zobrazit plný text záznamu

Report

Empirical and Experimental Perspectives on Big Data in Recommendation Systems: A Comprehensive Survey

Autor: Taha, Kamal, Yoo, Paul D., Taha, Aya

This survey paper provides a comprehensive analysis of big data algorithms in recommendation systems, addressing the lack of depth and precision in existing literature. It proposes a two-pronged approach: a thorough analysis of current algorithms and

Externí odkaz: http://arxiv.org/abs/2402.03368

Zobrazit plný text záznamu

Report

Unlocking Criminal Hierarchies: A Survey, Experimental, and Comparative Exploration of Techniques for Identifying Leaders within Criminal Networks

Autor: Taha, Kamal, Shoufan, Abdulhadi, Taha, Aya

This survey paper offers a thorough analysis of techniques and algorithms used in the identification of crime leaders within criminal networks. For each technique, the paper examines its effectiveness, limitations, potential for improvement, and futu

Externí odkaz: http://arxiv.org/abs/2402.03355

Zobrazit plný text záznamu

Report

A Comprehensive Survey of Text Classification Techniques and Their Research Applications: Observational and Experimental Insights

Autor: Taha, Kamal, Yoo, Paul D., Yeun, Chan, Taha, Aya

The exponential growth of textual data presents substantial challenges in management and analysis, notably due to high storage and processing costs. Text classification, a vital aspect of text mining, provides robust solutions by enabling efficient c

Externí odkaz: http://arxiv.org/abs/2401.12982

Zobrazit plný text záznamu

Report

Observational and Experimental Insights into Machine Learning-Based Defect Classification in Wafers

Autor: Taha, Kamal

This survey paper offers a comprehensive review of methodologies utilizing machine learning (ML) classification techniques for identifying wafer defects in semiconductor manufacturing. Despite the growing body of research demonstrating the effectiven

Externí odkaz: http://arxiv.org/abs/2310.10705

Zobrazit plný text záznamu

Akademický článek

GMB: An Efficient Query Processor for Biological Data

Autor: Taha Kamal, Elmasri Ramez

Publikováno v: Journal of Integrative Bioinformatics, Vol 8, Iss 2, Pp 130-147 (2011)

Bioinformatics applications manage complex biological data stored into distributed and often heterogeneous databases and require large computing power. These databases are too big and complicated to be rapidly queried every time a user submits a quer

Externí odkaz: https://doaj.org/article/20349af2ceef4e07ab2f3655b80492f2