Research Area:  Machine Learning

Abstract:

To achieve state-of-the-art performance, keyphrase extraction systems rely on domain-specific knowledge and sophisticated features. In this paper, we propose a neural network architecture based on a Bidirectional Long Short-Term Memory Recurrent Neural Network that is able to detect the main topics on the input documents without the need of defining new hand-crafted features. A preliminary experimental evaluation on the well-known INSPEC dataset confirms the effectiveness of the proposed solution.

Keywords:  
Lstm
Recurrent Neural Network
Keyphrase Extraction
neural network architecture
Machine Learning
Deep Learning

Author(s) Name:  Marco Basaldella, Elisa Antolli, Giuseppe Serra & Carlo Tasso

Publisher name:  Springer

DOI:   10.1007/978-3-319-73165-0_18

Volume Information:  

Paper Link:   https://link.springer.com/chapter/10.1007/978-3-319-73165-0_18