Automatic Summarization Using Terminological and Semantic Resources

被引：0
|
作者：
Vivaldi, Jorge [1 ]
da Cunha, Iria [1 ,2 ]
Torres-Moreno, Juan-Manuel [2 ,3 ]
Velazquez-Morales, Patricia [4 ]
机构：
[1] Inst Univ Lingist Aplicada UPF, Barcelona 08018, Spain
[2] Lab Informat Avignon UAPV, F-84911 Avignon, France
[3] Ecole Polytech, Montreal, PQ H3C 3A7, Canada
[4] VM Labs, F-8400 Avignon, France
来源：
LREC 2010 - SEVENTH INTERNATIONAL CONFERENCE ON LANGUAGE RESOURCES AND EVALUATION | 2010年
关键词：
ABSTRACTS;
D O I：
暂无
中图分类号：
H [语言、文字];
学科分类号：
05 ;
摘要：
In this paper we present a new algorithm for automatic summarization of specialized texts combining terminological and semantic resources: a term extractor and an ontology. The term extractor provides the list of the terms that are present in the text together their corresponding termhood. The ontology is used to calculate the semantic similarity among the terms found in the main body and those present in the document title. The phrases with the highest score are chosen to take part of the final summary. We evaluate the algorithm with ROUGE, comparing the resulting summaries with the summaries of other summarizers. The sentence selection algorithm was also tested as part of a standalone summarizer. It obtains good results, but there is a space for improvement.
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页码：3105 / 3112
页数：8
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