Du , M & Yangarber , R 2015 , Acquisition of Domain-specific Patterns for Single Document Summarization and Information Extraction . in Y Zhou (ed.) , Proceedings of the The Second International Conference on Artificial Intelligence and Pattern Recognition, Shenzhen, China, 2015 . The Society of Digital Information and Wireless Communications (SDIWC) , International Conference on Artificial Intelligence and Pattern Recognition , ShenZhen , China , 16/04/2015 .
Title: | Acquisition of Domain-specific Patterns for Single Document Summarization and Information Extraction |
Author: | Du, Mian; Yangarber, Roman |
Other contributor: | Zhou, Yimin |
Contributor organization: | Department of Computer Science Computational Linguistics research group / Roman Yangarber |
Publisher: | The Society of Digital Information and Wireless Communications (SDIWC) |
Date: | 2015-04-17 |
Language: | eng |
Number of pages: | 10 |
Belongs to series: | Proceedings of the The Second International Conference on Artificial Intelligence and Pattern Recognition, Shenzhen, China, 2015 |
ISBN: | 978-1-941968-09-3 |
URI: | http://hdl.handle.net/10138/155662 |
Abstract: | Single-document summarization aims to reduce the size of a text document while preserving the most important information. Much work has been done on open-domain summarization. This paper presents an automatic way to mine domain-specific patterns from text documents. With a small amount of effort required for manual selection, these patterns can be used for domain-specific scenario-based document summarization and information extraction. Our evaluation shows that scenario-based document summarization can both filter irrelevant documents and create summaries for relevant documents within the specified domain. |
Description: | AIPR 2015. |
Subject: |
113 Computer and information sciences
Information Extraction Machine learning Data Mining |
Peer reviewed: | Yes |
Usage restriction: | openAccess |
Self-archived version: | acceptedVersion |
Total number of downloads: Loading...
Files | Size | Format | View |
---|---|---|---|
2015_aipr_patterns.pdf | 651.3Kb |
View/ |