Natural Language Processing (NLP) has become a foundational technology in modern web applications, significantly enhancing human–computer interaction (HCI) through more intuitive and intelligent communication systems. NLP encompasses computational techniques that enable machines to understand, interpret and generate human language, evolving from rule-based approaches to advanced machine learning and deep learning models. The integration of large language models and conversational AI has further expanded the scope of NLP, enabling sophisticated text processing, tokenisation, named entity recognition and sentiment analysis within web environments. These advancements have transformed digital interaction by allowing users to engage with systems through natural language queries, voice-enabled interfaces and adaptive conversational platforms. The incorporation of NLP into web-based systems has led to the widespread adoption of chatbots, virtual assistants, intelligent search engines and cloud-based NLP services. These technologies facilitate personalised user experiences, multilingual communication and reduced cognitive effort in navigating digital platforms. Applications of NLP span across e-commerce recommendation systems, automated customer support, e-learning platforms and social media analytics, demonstrating its versatility and relevance in diverse domains. Despite these benefits, several challenges persist, including ambiguity in language interpretation, ethical concerns related to data privacy, inherent biases in training data and the high computational cost associated with large-scale models. These limitations highlight the need for continued research and responsible implementation. Future directions in NLP focus on advancements in generative AI, real-time processing through edge computing, improved contextual and emotional intelligence, and integration with emerging technologies such as the Internet of Things and augmented reality.
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E. Bethel Okpomu
The Federal Polytechnic, Ado-Ekiti
O. Samuel Ogoro
The Federal Polytechnic, Ado-Ekiti
The Federal Polytechnic, Ado-Ekiti
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Analyzing shared references across papers
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Okpomu et al. (Tue,) studied this question.
synapsesocial.com/papers/6a1fc616dee9eb8c0dce75f9 — DOI: https://doi.org/10.5281/zenodo.20488449