Exploiting novelty, coverage and balance for topic-focused multi-document summarization

Authors:
Xuan Li;Yi-Dong Shen;Liang Du;Chen-Yan Xiong
Affiliations:
Chinese Academy of Sciences, Beijing, China;Chinese Academy of Sciences, Beijing, China;Chinese Academy of Sciences, Beijing, China;Chinese Academy of Sciences, Beijing, China
Venue:
CIKM '10 Proceedings of the 19th ACM international conference on Information and knowledge management
Year:
2010

Citing 8
Cited 5

The use of MMR, diversity-based reranking for reordering documents and producing summaries

Proceedings of the 21st annual international ACM SIGIR conference on Research and development in information retrieval
A new approach to unsupervised text summarization

Proceedings of the 24th annual international ACM SIGIR conference on Research and development in information retrieval
Generic summarization and keyphrase extraction using mutual reinforcement principle and sentence clustering

SIGIR '02 Proceedings of the 25th annual international ACM SIGIR conference on Research and development in information retrieval
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
Multi-document summarization using cluster-based link analysis

Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval
Novelty and diversity in information retrieval evaluation

Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval
Enhancing diversity, coverage and balance for summarization through structure learning

Proceedings of the 18th international conference on World wide web
Manifold-ranking based topic-focused multi-document summarization

IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence

Discovering collective viewpoints on micro-blogging events based on community and temporal aspects

ADMA'11 Proceedings of the 7th international conference on Advanced Data Mining and Applications - Volume Part I
Collective viewpoint identification of low-level participation

APWeb'12 Proceedings of the 14th Asia-Pacific international conference on Web Technologies and Applications
Query-focused multi-document summarization based on query-sensitive feature space

Proceedings of the 21st ACM international conference on Information and knowledge management
Exploiting relevance, coverage, and novelty for query-focused multi-document summarization

Knowledge-Based Systems
Identification of collective viewpoints on microblogs

Data & Knowledge Engineering

Quantified Score

Hi-index	0.00

Visualization

Abstract

Novelty, coverage and balance are important requirements in topic-focused summarization, which to a large extent determine the quality of a summary. In this paper, we propose a novel method that incorporates these requirements into a sentence ranking probability model. It differs from the existing methods in that the novelty, coverage and balance requirements are all modeled w.r.t. a given topic, so that summaries are highly relevant to the topic and at the same time comply with topic-aware novelty, coverage and balance. Experimental results on the DUC 2005, 2006 and 2007 benchmark data sets demonstrate the effectiveness of our method.