Term-weighting approaches in automatic text retrieval
Information Processing and Management: an International Journal
A trainable document summarizer
SIGIR '95 Proceedings of the 18th annual international ACM SIGIR conference on Research and development in information retrieval
Information Processing and Management: an International Journal - Special issue: summarizing text
New Methods in Automatic Extracting
Journal of the ACM (JACM)
Learning Approaches for Detecting and Tracking News Events
IEEE Intelligent Systems
Fractal summarization: summarization based on fractal theory
Proceedings of the 26th annual international ACM SIGIR conference on Research and development in informaion retrieval
The TIPSTER SUMMAC Text Summarization Evaluation
EACL '99 Proceedings of the ninth conference on European chapter of the Association for Computational Linguistics
Discovering evolutionary theme patterns from text: an exploration of temporal text mining
Proceedings of the eleventh ACM SIGKDD international conference on Knowledge discovery in data mining
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
The automatic creation of literature abstracts
IBM Journal of Research and Development
Multi-document summarization for terrorism information extraction
ISI'06 Proceedings of the 4th IEEE international conference on Intelligence and Security Informatics
ICADL'05 Proceedings of the 8th international conference on Asian Digital Libraries: implementing strategies and sharing experiences
Multi-document summarization for e-learning
ICHL'09 Proceedings of the Second international conference on Hybrid Learning and Education
| Hi-index | 0.00 |
Hierarchical summarization technique summarizes a large document based on the hierarchical structure and salient features of the document. Previous study has shown that hierarchical summarization is a promising technique which can effectively extract the most important information from the source document. Hierarchical summarization has been extended to summarization of multiple documents. Three hierarchical structures were proposed to organize a set of related documents. This paper investigates the impact of document structure on hierarchical summarization. The results show that the hierarchical summarization of multiple documents organized in hierarchical structure outperforms other multi-document summarization systems without using the hierarchical structure. Moreover, the hierarchical summarization by event topics extracts a set of sentences significantly different from hierarchical summarization of other hierarchical structures and performs the best when the summary is highly-compressed.