ITR: Information Fusion Across Multiple Text Sources: A Common Theory

Regents Of The University Of Michigan - Ann Arbor, Ann Arbor MI

Investigators

Abstract

A common theory of information fusion across multiple text sources is to be developed. Three main tasks are undertaken: (a) robust techniques for identifying structure across sets of related textual documents in arbitrary domains are developed and used to produce graph representations of the document sets, (b) an environment in which users can specify their summarization preferences is created, and (c) graph-based methods are applied to produce personalized multi-document summaries of clusters of the related documents based on the users' priorities. Cross-document structure is based on features such as paraphrasing, contradiction, change of perspective, and complementation. A large-scale taxonomy of cross-document links is being investigated. Providing users with personalized abstracts of large amounts of critical textual information is expected to speed up and otherwise facilitate their access to the Web. Large-scale deployment of a Web-based summarization system based on cross-document structure is planned and is expected to be used by millions of users.