Can AI help me determine the key words in the thesis?

Yes, artificial intelligence (AI) offers effective tools to assist researchers in identifying keywords for their academic theses. AI systems, particularly those employing Natural Language Processing (NLP) techniques, analyze large volumes of text data. Keyphrase extraction algorithms (e.g., TF-IDF, RAKE, or sophisticated transformer-based models) can rapidly scan the thesis text, identifying statistically frequent or semantically salient terms and phrases significant to the core content. While automated tools provide objective suggestions based on computational metrics, their accuracy depends significantly on input text quality and clarity, requiring the inherent expertise of the researcher. Therefore, AI output should be rigorously reviewed and refined to ensure keywords precisely capture the study's essential concepts, methodologies, and contributions. Utilizing AI for this task significantly enhances efficiency by automating the initial scan of potentially lengthy documents. It provides valuable, data-driven insights, uncovering terms the author may have overlooked. This aids in improving thesis discoverability through search engines and academic databases and ensures the selected keywords accurately reflect the research focus, aligning better with relevant literature and potential readers. AI acts as a powerful assistive tool in optimizing this critical metadata aspect.