Keyphrase Extraction

Keyphrase extraction aims to automatically identify the most important phrases summarizing a document's content, facilitating tasks like information retrieval and text summarization. Current research heavily utilizes pre-trained language models (like BERT and BART), often incorporating techniques such as self-attention, contrastive learning, and graph embeddings to improve performance, particularly for long documents and cross-domain applications. These advancements are crucial for efficiently managing the ever-increasing volume of digital text, enabling better organization, search, and understanding of information across diverse fields.