Abstract
Unsupervised extractive summarization do not need parallel corpus pairs for training, so they are widely used in many scenarios. Many unsupervised extractive summarization methods usually lose the context information of sentences. Based on the context information, this paper proposes a model of unsupervised extractive summarization. At the same time, we tested many ways to express the context information. We also studied the relationship between sentences in the abstract. We have proved that the context information and the relationship between the sentences are very helpful to the task and we developed an unsupervised summarization system without any training.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
