Single Document Summarization based on Nested Tree Structure
Yuta Kikuchi,Tsutomu Hirao,Hiroya Takamura,Manabu Okumura,Masaaki Nagata +4 more
- 01 Jun 2014
- Vol. 2, pp 315-320
TL;DR: The results from an empirical evaluation revealed that the method based on the trimming of the nested tree significantly improved the summarization of texts.
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Abstract: Many methods of text summarization combining sentence selection and sentence compression have recently been proposed. Although the dependency between words has been used in most of these methods, the dependency between sentences, i.e., rhetorical structures, has not been exploited in such joint methods. We used both dependency between words and dependency between sentences by constructing a nested tree, in which nodes in the document tree representing dependency between sentences were replaced by a sentence tree representing dependency between words. We formulated a summarization task as a combinatorial optimization problem, in which the nested tree was trimmed without losing important content in the source document. The results from an empirical evaluation revealed that our method based on the trimming of the nested tree significantly improved the summarization of texts.
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References
•Proceedings Article
ROUGE: A Package for Automatic Evaluation of Summaries
Chin-Yew Lin
- 25 Jul 2004
TL;DR: Four different RouGE measures are introduced: ROUGE-N, ROUge-L, R OUGE-W, and ROUAGE-S included in the Rouge summarization evaluation package and their evaluations.
Rhetorical Structure Theory : Toward a Functional Theory of Text Organization
TL;DR: Rhetorical Structure Theory (RST) as mentioned in this paper is a descriptive theory of a major aspect of the organization of natural text, which is a linguistically useful method for describing natural texts, characterizing their Structure primarily in terms of relations that hold between parts of the text.
4.1K
Building a discourse-tagged corpus in the framework of Rhetorical Structure Theory
Lynn Carlson,Daniel Marcu,Mary Ellen Okurowski +2 more
- 01 Sep 2001
TL;DR: Working in the framework of Rhetorical Structure Theory, a large annotated resource with very high consistency is created, using a well-defined methodology and protocol to enable researchers to develop empirically grounded, discourse-specific applications.
817
•Proceedings Article
Statistics-Based Summarization - Step One: Sentence Compression
Kevin Knight,Daniel Marcu +1 more
- 30 Jul 2000
TL;DR: This paper focuses on sentence compression, a simpler version of this larger challenge, and aims to achieve two goals simultaneously: the compressions should be grammatical, and they should retain the most important pieces of information.
•Proceedings Article
Towards Coherent Multi-Document Summarization
Janara Christensen,Stephen Soderland,Oren Etzioni +2 more
- 01 Jun 2013
TL;DR: G-FLOW is evaluated on Mechanical Turk, and it is found that it generates dramatically better summaries than an extractive summarizer based on a pipeline of state-of-the-art sentence selection and reordering components, underscoring the value of the joint model.