The paper presents a multi-document summarization system which builds companyspecific summaries from a collection of financial news such that the extracted sentences contain novel and relevant information about the corresponding organization. The user’s familiarity with the company’s profile is assumed. The goal of such summaries is to provide information useful for the short-term trading of the corresponding company, ., to facilitate the inference from news to stock price movement in the next day. We introduce a novel query (., company name) expansion method and a simple unsupervized algorithm for sentence ranking. The system shows promising results in comparison with.
