@techreport{oai:ipsj.ixsq.nii.ac.jp:00197764,
 author = {山田, 尚志 and 田中, 聡 and Hisashi, Yamada and Satoshi, Tanaka},
 issue = {4},
 month = {Jun},
 note = {SNS などに含まれる文からセンチメントの把握や顧客満足度を推計するための感情分析で利用する文の極性判定において，文中に含まれる話題の集合と極性を持つ単語との文字列間距離に着目し，話題の集合に対して極性を付与するシステムを検討した．本システムは SVM と極性を持つ単語辞書を利用し，話題を親ノード，極性を持つ単語を子ノードとした二分木を構築，単語間の距離が短い親子関係から極性を判定する機能を実現した．評価により Twitter のような短文で崩れた日本語が多い場合でも，ツイート内の話題に対する極性を判定できることを示した．, In the determination of the polarity of a sentence used for understanding of sentiment from sentences included in SNS etc. and emotion analysis for estimating customer satisfaction, the distance between character strings between a set of topics included in the sentence and a word having polarity Pay attention. We examined a system that gives polarity to a set of topics. This system uses a word dictionary with SVM and polarity, and constructs a binary tree with a topic as a parent node and a word with polarity as a child node, and realizes the function of judging polarity from parent-child relationship with short distance between words . It was shown that even if there are many broken Japanese in a short sentence like Twitter, the evaluation can determine the polarity for the topic in the tweet.},
 title = {単語間距離を利用した極性判定手法の提案と実装},
 year = {2019}
}