Mutual-reinforcement document summarization using embedded graph based sentence clustering for storytelling

Authors:
Zhengchen Zhang;Shuzhi Sam Ge;Hongsheng He
Affiliations:
Department of Electrical & Computer Engineering, National University of Singapore, Singapore 117576, Singapore and Social Robotics Lab, Interactive Digital Media Institute, National University of ...;Department of Electrical & Computer Engineering, National University of Singapore, Singapore 117576, Singapore and Social Robotics Lab, Interactive Digital Media Institute, National University of ...;Department of Electrical & Computer Engineering, National University of Singapore, Singapore 117576, Singapore and Social Robotics Lab, Interactive Digital Media Institute, National University of ...
Venue:
Information Processing and Management: an International Journal
Year:
2012

Citing 24
Cited 2

Generic text summarization using relevance measure and latent semantic analysis

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
Summarization beyond sentence extraction: a probabilistic approach to sentence compression

Artificial Intelligence
The diversity-based approach to open-domain text summarization

Information Processing and Management: an International Journal
Document clustering based on non-negative matrix factorization

Proceedings of the 26th annual international ACM SIGIR conference on Research and development in informaion retrieval
The automated acquisition of topic signatures for text summarization

COLING '00 Proceedings of the 18th conference on Computational linguistics - Volume 1
Fast generation of abstracts from general domain text corpora by extracting relevant sentences

COLING '96 Proceedings of the 16th conference on Computational linguistics - Volume 2
Web-page classification through summarization

Proceedings of the 27th annual international ACM SIGIR conference on Research and development in information retrieval
Centroid-based summarization of multiple documents

Information Processing and Management: an International Journal
Answer extraction, semantic clustering, and extractive summarization for clinical question answering

ACL-44 Proceedings of the 21st International Conference on Computational Linguistics and the 44th annual meeting of the Association for Computational Linguistics
Using random walks for question-focused sentence retrieval

HLT '05 Proceedings of the conference on Human Language Technology and Empirical Methods in Natural Language Processing
Topic discovery based on text mining techniques

Information Processing and Management: an International Journal
Text mining techniques for patent analysis

Information Processing and Management: an International Journal
Generating gene summaries from biomedical literature: A study of semi-structured summarization

Information Processing and Management: an International Journal
Single-document and multi-document summarization techniques for email threads using sentence compression

Information Processing and Management: an International Journal
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 via sentence-level semantic analysis and symmetric matrix factorization

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
Automatic generic document summarization based on non-negative matrix factorization

Information Processing and Management: an International Journal
Weighted locally linear embedding for dimension reduction

Pattern Recognition
LexRank: graph-based lexical centrality as salience in text summarization

Journal of Artificial Intelligence Research
Document summarization using conditional random fields

IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Neighborhood linear embedding for intrinsic structure discovery

Machine Vision and Applications
Using topic themes for multi-document summarization

ACM Transactions on Information Systems (TOIS)

Combining co-clustering with noise detection for theme-based summarization

ACM Transactions on Speech and Language Processing (TSLP)
PSG: a two-layer graph model for document summarization

Frontiers of Computer Science: Selected Publications from Chinese Universities

Quantified Score

Hi-index	0.00

Visualization

Abstract

In this paper, a document summarization framework for storytelling is proposed to extract essential sentences from a document by exploiting the mutual effects between terms, sentences and clusters. There are three phrases in the framework: document modeling, sentence clustering and sentence ranking. The story document is modeled by a weighted graph with vertexes that represent sentences of the document. The sentences are clustered into different groups to find the latent topics in the story. To alleviate the influence of unrelated sentences in clustering, an embedding process is employed to optimize the document model. The sentences are then ranked according to the mutual effect between terms, sentence as well as clusters, and high-ranked sentences are selected to comprise the summarization of the document. The experimental results on the Document Understanding Conference (DUC) data sets demonstrate the effectiveness of the proposed method in document summarization. The results also show that the embedding process for sentence clustering render the system more robust with respect to different cluster numbers.