@techreport{oai:ipsj.ixsq.nii.ac.jp:00048857,
 author = {加藤, 直人 and Naoto, Katoh},
 issue = {63(1998-NL-126)},
 month = {Jul},
 note = {日本語ニュースを自動要約する際の言語知識となる，局所的要約知識を自動獲得する手法について述べる．局所的要約知識は置換知識と置換条件からなり，文字，単語，文節レベルでの言い換えを規定する．本手法では原文とその要約文とのペアからなるコーパスを使って要約知識を自動獲得する．自動獲得では，はじめに原文中の単語と要約文中の単語のすべての組み合わせに対して単語間の距離を計算し，DPマッチングによって最適な単語対応を求める．その結果より，置換知識は単語対応上で不一致となる単語列として得る．一方，置換条件は置換知識の前後nグラムの単語列として得る．NHKニュースを使って局所的要約知識の自動獲得を行い，要約知識を評価する実験を行った．, This paper proposes a new approach to acquiring linguistic knowledge that plays an important role in summarizing parts of news sentences. The linguistic knowledge, which is composed of transformation knowledge and transformation condition, can provide linguistic constraint of transforming characters, words, Bunsetsu-phrases in summarizing Japanese sentences. The proposed method analyzes original news sentences and the human-summarized ones by Japanese morphological analyzer, and aligns words in the original sentences with words in the summarized ones by DP matching based on distances between the words. Transformation knowledge is acquired as the result of the difference and transformation condition is extracted as n-gram words located near transformation knowledge. We acquired linguistic knowledge from NHK news corpus and conducted a series of experiments to evaluate the linguistic knowledge.},
 title = {ニュース文要約のための局所的要約知識獲得とその評価},
 year = {1998}
}