DUC in context

Authors:
Paul Over;Hoa Dang;Donna Harman
Affiliations:
Retrieval Group, Information Access Division, National Institute of Standards and Technology, Gaithersburg, MD 20899-8940, United States;Retrieval Group, Information Access Division, National Institute of Standards and Technology, Gaithersburg, MD 20899-8940, United States;Retrieval Group, Information Access Division, National Institute of Standards and Technology, Gaithersburg, MD 20899-8940, United States
Venue:
Information Processing and Management: an International Journal
Year:
2007

Citing 4
Cited 13

The Theory and Practice of Discourse Parsing and Summarization

The Theory and Practice of Discourse Parsing and Summarization
The TIPSTER SUMMAC Text Summarization Evaluation

EACL '99 Proceedings of the ninth conference on European chapter of the Association for Computational Linguistics
NewsInEssence: a system for domain-independent, real-time news clustering and multi-document summarization

HLT '01 Proceedings of the first international conference on Human language technology research
Tracking and summarizing news on a daily basis with Columbia's Newsblaster

HLT '02 Proceedings of the second international conference on Human Language Technology Research

Query-sensitive mutual reinforcement chain and its application in query-oriented multi-document summarization

Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval
GA, MR, FFNN, PNN and GMM based models for automatic text summarization

Computer Speech and Language
Query-based opinion summarization for legal blog entries

Proceedings of the 12th International Conference on Artificial Intelligence and Law
Update summarization based on novel topic distribution

Proceedings of the 9th ACM symposium on Document engineering
Performance confidence estimation for automatic summarization

EACL '09 Proceedings of the 12th Conference of the European Chapter of the Association for Computational Linguistics
Co-feedback ranking for query-focused summarization

ACLShort '09 Proceedings of the ACL-IJCNLP 2009 Conference Short Papers
Automatically evaluating content selection in summarization without human models

EMNLP '09 Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing: Volume 1 - Volume 1
Automatic evaluation of linguistic quality in multi-document summarization

ACL '10 Proceedings of the 48th Annual Meeting of the Association for Computational Linguistics
Structural features for predicting the linguistic quality of text: applications to machine translation, automatic summarization and human-authored text

Empirical methods in natural language generation
CorrRank: update summarization based on topic correlation analysis

ICIC'10 Proceedings of the Advanced intelligent computing theories and applications, and 6th international conference on Intelligent computing
Multilingual summarization evaluation without human models

COLING '10 Proceedings of the 23rd International Conference on Computational Linguistics: Posters
Text summarisation in progress: a literature review

Artificial Intelligence Review
An assessment of the accuracy of automatic evaluation in summarization

Proceedings of Workshop on Evaluation Metrics and System Comparison for Automatic Summarization

Quantified Score

Hi-index	0.00

Visualization

Abstract

Recent years have seen increased interest in text summarization with emphasis on evaluation of prototype systems. Many factors can affect the design of such evaluations, requiring choices among competing alternatives. This paper examines several major themes running through three evaluations: SUMMAC, NTCIR, and DUC, with a concentration on DUC. The themes are extrinsic and intrinsic evaluation, evaluation procedures and methods, generic versus focused summaries, single- and multi-document summaries, length and compression issues, extracts versus abstracts, and issues with genre.