Multidocument Summarization via Information Extraction
Abstract
We present and evaluate the initial version of RIPTIDES, a system that combines information extraction, extraction-based summarization, and natural language generation to support user directed multidocument summarization. Although recent years has seen increased and successful research efforts in the areas of single-document summarization, multidocument summarization, and information extraction, very few investigations have explored the potential of merging summarization and information extraction techniques. This paper presents and evaluates the initial version of RIPTIDES, a system that combines information extraction (IE), extraction-based summarization, and natural language generation to support user directed multidocument summarization. (RIPTIDES stands for RapIdly Portable Translingual Information extraction and interactive multiDocumEnt Summarization.) Following [10], we hypothesize that IE-supported summarization will enable the generation of more accurate and targeted summaries in specific domains than is possible with current domain-independent techniques. In the sections below, we describe the initial implementation and evaluation of the RIPTIDES IE-supported summarization system. We conclude with a brief discussion of related and ongoing work.
Document Details
- Document Type
- Technical Report
- Publication Date
- Jan 01, 2001
- Accession Number
- ADA457772
Entities
People
- Claire Cardie
- David Pierce
- Kiri Wagstaff
- Michael J. White
- Tanya Korelsky
- Vincent Ng