UniKeyphrase: A Unified Extraction and Generation Framework for Keyphrase Prediction

Keyphrase Prediction (KP) task aims at predicting several keyphrases that can summarize the main idea of the given document. Mainstream KP methods can be categorized into purely generative approaches and integrated models with extraction and generation. However, these methods either ignore the diversity among keyphrases or only weakly capture the relation across tasks implicitly. In this paper, we propose UniKeyphrase, a novel end-to-end learning framework that jointly learns to extract and generate keyphrases. In UniKeyphrase, stacked relation layer and bagof-words constraint are proposed to fully exploit the latent semantic relation between extraction and generation in the view of model structure and training process, respectively. Experiments on KP benchmarks demonstrate that our joint approach outperforms mainstream methods by a large margin. 1 * Equal contribution. 1 Our code is available on https://github.com/thinkwee/UniKeyphrase Document: On selecting an optimal wavelet for detecting singularities in traffic and vehicular data. …… applications of wavelet transform s ( wts ) in traffic engineering have been introduced however , …… , second order difference , oblique cumulative curve , and short time fourier transform ) . it then mathematically describes wts ability to detect singularities in traffic data . …… , it is shown that selecting a suitable wavelet largely depends on the specific research topic , and that the mexican hat wavelet generally gives a satisfactory performance in detecting singularities in traffic and vehicular data .