Relevance Modeling for Microblog Summarization

Authors

  • Sanda Harabagiu University of Texas at Dallas
  • Andrew Hickl Language Computer Corporation

Abstract

This paper introduces a new type of summarization task, known as microblog summarization, which aims to synthesize content from multiple microblog posts on the same topic into a human-readable prose description of fixed length. Our approach leverages (1) a generative model which induces event structures from text and (2) a user behavior model which captures how users convey relevant content.

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Published

2021-08-03

How to Cite

Harabagiu, S., & Hickl, A. (2021). Relevance Modeling for Microblog Summarization. Proceedings of the International AAAI Conference on Web and Social Media, 5(1), 514-517. Retrieved from https://ojs.aaai.org/index.php/ICWSM/article/view/14190