Abstract. Evaluation is one of the hardest tasks in automatic text summarization. It is perhaps even harder to determine how much a particular component of a summarization system c...
In this paper we present a framework for spoken recommendation systems. To provide reliable recommendations to users, we incorporate a review summarization technique which extract...
Documents often contain inherently many concepts reflecting specific and generic aspects. To automatically generate a short summary text of documents on similar topics, it is im...
We present a cut and paste based text summarizer, which uses operations derived from an analhuman written abstracts. The summarizer edits extracted sentences, using reduction to r...
Due to the lack of annotated data sets, there are few studies on machine learning based approaches to extract named entities (NEs) in clinical text. The 2009 i2b2 NLP challenge is...