<--- Back to Details
First PageDocument Content
Statistics / Automatic summarization / Expectation–maximization algorithm / Finitary relation / Multi-document summarization / Sentence extraction / ROUGE / Mode / Decision making / Natural language processing / Computational linguistics / Science
Date: 2013-11-07 08:31:50
Statistics
Automatic summarization
Expectation–maximization algorithm
Finitary relation
Multi-document summarization
Sentence extraction
ROUGE
Mode
Decision making
Natural language processing
Computational linguistics
Science

Focused Meeting Summarization via Unsupervised Relation Extraction

Add to Reading List

Source URL: www.cs.cornell.edu

Download Document from Source Website

File Size: 289,64 KB

Share Document on Facebook

Similar Documents

Multi-source annotation projection of coreference chains: assessing strategies and testing opportunities Yulia Grishina and Manfred Stede Applied Computational Linguistics FSP Cognitive Science University of Potsdam

DocID: 1vrep - View Document

Proceedings of the 40th Annual Meeting of the Association for Computational Linguistics (ACL), Philadelphia, July 2002, pp.

DocID: 1vn1Q - View Document

NODALIDA 2009 th 17 Nordic Conference of Computational Linguistics Kristiina Jokinen

DocID: 1vkzQ - View Document

Concepts and properties in word spaces* Marco Baroni & Alessandro Lenci Properties play a central role in most theories of conceptual knowledge. Since computational models derived from word co-occurrence statistics have

DocID: 1vcjQ - View Document

The ACL Anthology Reference Corpus: A Reference Dataset for Bibliographic Research in Computational Linguistics Steven Bird1 , Robert Dale2 , Bonnie J. Dorr3 , Bryan Gibson4 , Mark T. Joseph4 , Min-Yen Kan5† , Dongwon

DocID: 1v63z - View Document