Paper: Company-Oriented Extractive Summarization of Financial News

ACL ID E09-1029
Title Company-Oriented Extractive Summarization of Financial News
Venue Annual Meeting of The European Chapter of The Association of Computational Linguistics
Session Main Conference
Year 2009
Authors

The paper presents a multi-document sum- marization system which builds company- specific summaries from a collection of fi- nancial news such that the extracted sen- tences contain novel and relevant infor- mation about the corresponding organiza- tion. The user’s familiarity with the com- pany’s profile is assumed. The goal of such summaries is to provide information useful for the short-term trading of the cor- responding company, i.e., to facilitate the inference from news to stock price move- ment in the next day. We introduce a novel query (i.e., company name) expan- sion method and a simple unsupervized al- gorithm for sentence ranking. The sys- tem shows promising results in compari- son with a competitive baseline.