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Using Key Phrases to Interpret Semantic Elements of Internet Texts
Abstract
This article discusses the significance of key phrases in unlocking the semantic characteristics of internet texts in obtaining pertinent information from the web. The main issue is with conventional key phrase or keyword-based retrieval systems, which do not account for subtle meaning and contextually conditioned expressions. The solution is to draw upon recent developments in Natural Language Processing (NLP), specifically transformer models such as BERT and GPT, to advance semantic evaluation. Key contributions include the incorporation of NLP techniques to refine document retrieval and semantic interpretation, emphasizing contextual understanding of web texts. Primary findings highlight the potential for NLP models to assist in dealing with challenges such as language uncertainty and cultural divergence and provide more effective and accurate semantic analysis processes for online environments. This article takes forward the development of improved language learners and NLP system tools, enabling them to better interpret and interact with online content that is rich in nature.
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