文章基本信息

标题：Automatic Summarization as a Combinatorial Optimization Problem
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作者：Tsutomu Hirao ; Jun Suzuki ; Hideki Isozaki 等
期刊名称：人工知能学会論文誌
印刷版ISSN：1346-0714
电子版ISSN：1346-8030
出版年度：2009
卷号：24
期号：2
页码：223-231
DOI：10.1527/tjsai.24.223
出版社：The Japanese Society for Artificial Intelligence
摘要：We derived the oracle summary with the highest ROUGE score that can be achieved by integrating sentence extraction with sentence compression from the reference abstract . The analysis results of the oracle revealed that summarization systems have to assign an appropriate compression rate for each sentence in the document. In accordance with this observation, this paper proposes a summarization method as a combinatorial optimization: selecting the set of sentences that maximize the sum of the sentence scores from the pool which consists of the sentences with various compression rates, subject to length constrains. The score of the sentence is defined by its compression rate, content words and positional information. The parameters for the compression rates and positional information are optimized by minimizing the loss between score of oracles and that of candidates. The results obtained from TSC-2 corpus showed that our method outperformed the previous systems with statistical significance.
关键词：text summarization ; sentence compression ; combinatorial optimization ; knapsack problem ; dynamic programming