Comparative Study of Domain Driven Terms Extraction Using Large Language Models

arXiv:2404.02330v1 Announce Type: new
Abstract: Keywords play a crucial role in bridging the gap between human understanding and machine processing of textual data. They are essential to data enrichment because they form the basis for detailed annotations that provide a more insightful and in-depth view of the underlying data. Keyword/domain driven term extraction is a pivotal task in natural language processing, facilitating information retrieval, document summarization, and content categorization. This review focuses on keyword extraction methods, emphasizing the use of …

abstract annotations arxiv cs.ai cs.cl data data enrichment domain extraction form gap human keywords language language models large language large language models machine processing role study terms textual type understanding view