Optimization-based content selection for opinion summarization

Authors:
Jackie Chi Kit Cheung;Giuseppe Carenini;Raymond T. Ng
Affiliations:
University of Toronto, Toronto, ON, Canada;University of British Columbia, Vancouver, BC, Canada;University of British Columbia, Vancouver, BC, Canada
Venue:
UCNLG+Sum '09 Proceedings of the 2009 Workshop on Language Generation and Summarisation
Year:
2009

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Abstract

We introduce a content selection method for opinion summarization based on a well-studied, formal mathematical model, the p-median clustering problem from facility location theory. Our method replaces a series of local, myopic steps to content selection with a global solution, and is designed to allow content and realization decisions to be naturally integrated. We evaluate and compare our method against an existing heuristic-based method on content selection, using human selections as a gold standard. We find that the algorithms perform similarly, suggesting that our content selection method is robust enough to support integration with other aspects of summarization.