Paper: Bayesian Query-Focused Summarization

ACL ID P06-1039
Title Bayesian Query-Focused Summarization
Venue Annual Meeting of the Association of Computational Linguistics
Session Main Conference
Year 2006

We present BAYESUM (for “Bayesian summarization”), a model for sentence ex- traction in query-focused summarization. BAYESUM leverages the common case in which multiple documents are relevant to a single query. Using these documents as re- inforcement for query terms, BAYESUM is not afflicted by the paucity of information in short queries. We show that approxi- mate inference in BAYESUM is possible on large data sets and results in a state- of-the-art summarization system. Further- more, we show how BAYESUM can be understood as a justified query expansion technique in the language modeling for IR framework.