Keyphrase Generation: A Multi-Aspect Survey
It provides a comprehensive overview for researchers in natural language processing, but is incremental as it synthesizes existing work without introducing new methods.
This survey examines both extractive and abstractive keyphrase generation methods, with a focus on recent neural network-based approaches, and releases a large dataset of scientific article metadata and keyphrases for the research community.
Extractive keyphrase generation research has been around since the nineties, but the more advanced abstractive approach based on the encoder-decoder framework and sequence-to-sequence learning has been explored only recently. In fact, more than a dozen of abstractive methods have been proposed in the last three years, producing meaningful keyphrases and achieving state-of-the-art scores. In this survey, we examine various aspects of the extractive keyphrase generation methods and focus mostly on the more recent abstractive methods that are based on neural networks. We pay particular attention to the mechanisms that have driven the perfection of the later. A huge collection of scientific article metadata and the corresponding keyphrases is created and released for the research community. We also present various keyphrase generation and text summarization research patterns and trends of the last two decades.