One Size Does Not Fit All: Generating and Evaluating Variable Number of Keyphrases
Xingdi Yuan, Tong Wang, Rui Meng, Khushboo Thaker, Peter Brusilovsky, Daqing He, Adam Trischler
Abstract
Different texts shall by nature correspond to different number of keyphrases. This desideratum is largely missing from existing neural keyphrase generation models. In this study, we address this problem from both modeling and evaluation perspectives.
Topics & Concepts
Computer scienceGenerative grammarText generationVariable (mathematics)Artificial intelligenceContrast (vision)Generative modelDiversity (politics)Natural language processingMathematicsSociologyMathematical analysisAnthropologyAdvanced Text Analysis TechniquesInformation Retrieval and Search Behavior