Relevance Modeling for Microblog Summarization
Sanda M. Harabagiu, Andrew Hickl
2021Proceedings of the International AAAI Conference on Web and Social Media49 citationsDOIOpen Access PDF
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.
Topics & Concepts
Automatic summarizationMicrobloggingSocial mediaComputer scienceRelevance (law)Generative grammarEvent (particle physics)Information retrievalTask (project management)Multi-document summarizationGenerative modelWorld Wide WebArtificial intelligenceEngineeringPolitical scienceSystems engineeringQuantum mechanicsPhysicsLawTopic ModelingNatural Language Processing TechniquesAdvanced Text Analysis Techniques