计算机工程与应用2019，Vol.55Issue(20)：95-100,6.DOI:10.3778/j.issn.1002-8331.1806-0372
Title加TextRank抽取关键句的情感分类研究
Research on Sentiment Classification of Title and TextRank Extracting Key Sentences
摘要
Abstract
Considering that different sentences have different degrees of importance in judging the sentiment tendency of a document, thus, distinguishing a key sentence and a specific sentence will help improve the performance of the senti-ment classification. Meanwhile, taking into account Title and contextual information, a sentiment analysis method SKTT based on Title and weighted TextRank is proposed to achieve effective sentiment analysis. Firstly, the contribution of Title is calculated according to the sentiment weight of the document Title, considering the impact of punctuation and semantic rules on sentiment orientation. Then, according to the idea of weighted TextRank algorithm, an sentiment sentence directed graph is constructed in the document body to extract key sentences. Finally, the sentiment tendency of all key sentences is calculated to achieve sentiment classification. Experimental results across four domains show that the performance of the SKTT method is significantly better than the Baseline method and has high efficiency.关键词
Title/TextRank算法/关键句/情感分类/语义规则Key words
Title/TextRank algorithm/key sentence/sentiment classification/semantic rules分类
信息技术与安全科学引用本文复制引用
郑诚,钱改林,章金平..Title加TextRank抽取关键句的情感分类研究[J].计算机工程与应用,2019,55(20):95-100,6.基金项目
安徽省高校自然科学研究重点项目(No.KJ2013A020). （No.KJ2013A020）
