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<p>Artificial Intelligence (AI) is a transformative technology that can embed intelligence and human-like behavior into systems and devices. To develop smart, intelligent, and automated systems that address current needs, it is essential to employ AI-based models. This paper explores various components of AI—visual, textual, interactive, functional, and analytical—that enhance the capabilities and intelligence of applications to solve real-world problems. Given the ever-changing and diverse nature of real-life issues and data, creating effective AI models presents significant challenges. This study examines how Machine Learning (ML) and Deep Learning (DL) techniques can be leveraged for Information Retrieval (IR) within the context of a smarter education system. It provides an overarching view of AI-based modeling and its potential to create intelligent systems in fields such as cybersecurity, smart cities, agriculture, healthcare, finance, and business. Furthermore, the paper discusses research challenges related to AI modeling and offers insights for decision-makers in various application fields on employing ML and DL to enhance educational systems.</p>

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Towards a smarter education system: an investigation into ML and DL for information retrieval

  • 期刊论文

  • 发表日期：

    2025年4月16日

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  • Subhabrata Sengupta,
  • Satyajit Chakrabarti

摘要

Artificial Intelligence (AI) is a transformative technology that can embed intelligence and human-like behavior into systems and devices. To develop smart, intelligent, and automated systems that address current needs, it is essential to employ AI-based models. This paper explores various components of AI—visual, textual, interactive, functional, and analytical—that enhance the capabilities and intelligence of applications to solve real-world problems. Given the ever-changing and diverse nature of real-life issues and data, creating effective AI models presents significant challenges. This study examines how Machine Learning (ML) and Deep Learning (DL) techniques can be leveraged for Information Retrieval (IR) within the context of a smarter education system. It provides an overarching view of AI-based modeling and its potential to create intelligent systems in fields such as cybersecurity, smart cities, agriculture, healthcare, finance, and business. Furthermore, the paper discusses research challenges related to AI modeling and offers insights for decision-makers in various application fields on employing ML and DL to enhance educational systems.