We demonstrate TextRank -a system for unsupervised extractive summarization that relies on the application of iterative graphbased ranking algorithms to graphs encoding the cohesive structure of a text. An important characteristic of the system is that it does not rely on any language-specific knowledge resources or any manually constructed training data, and thus it is highly portable to new languages or domains.
Erkan and Radev (2004) and REF introduced approaches for unsupervised extractive summarization that rely on the application of iterative graph based ranking algorithms.
Language Independent Extractive Summarization
Annual Meeting Of The Association For Computational Linguistics - Interactive Poster And Demonstration Sessions
Computer Science