Work

Centroid-based summarization of multiple documents: sentence extraction, utility-based evaluation, and user studies

Year: 2000

Type: conference-paper

Abstract: We present a multi-document summarizer, called MEAD, which generates summaries using cluster centroids produced by a topic detection and tracking system. We also describe two new techniques, based on sentence utility and subsumption, which we have applied to the evaluation of both single and multiple document summaries. Finally, we describe two user studies that test our models of multi-document summarization.

Source: NAACL-ANLP Workshop on Automatic Summarization

DOI: 10.3115/1117575.1117578

Authors: Dragomir R. Radev, Hongyan Jing, Malgorzata Budzikowska

Institutions: University of Michigan, Columbia University, IBM (United States), IBM Research - Thomas J. Watson Research Center

Language: English

Topic: Advanced Text Analysis Techniques

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: bronze

OpenAlex ID: W2128672521

FWCI: 17.08

Cites: 14

Cited by: 510

Related to: 10