When I planned this book in 1999, it was intended to be a survey of current work in text
summarization. The survey would discuss various efforts in the context of a framework for …

This paper proposes two approaches to address text summarization: modified corpus-based
approach (MCBA) and LSA-based TRM approach (LSA+ TRM). The first is a trainable …

We discuss technology to help a person monitor changes in news coverage over time. We
define temporal summaries of news stories as extracting a single sentence from each event …

This chapter examines the nature of semantic relations and their main applications in
information science. The nature and types of semantic relations are discussed from the …

The rises of the life index quality together with the medical technology improvement lead to a
longer life expectancy. Thus a better health care program, especially for elderly, is needed …

This article presents a multidocument, multilingual, theme-based summarization system
based on modeling text cohesion (story flow). Conventional extractive summarization …

Abstract We propose Hidden Markov models with unsupervised training for extractive
summarization. Extractive summarization selects salient sentences from documents to be …

Biomedical literature incorporates millions of figures, which are a rich and important
knowledge resource for biomedical researchers. Scientists need access to the figures and …

The pursuit of methods to summarize text automatically has been under way since the
1950s, but the World Wide Web and other forces behind the information explosion of the last …

New event detection (NED), which is crucial to firms' environmental surveillance, requires
timely access to and effective analysis of live streams of news articles from various online …