国防科技大学学报
國防科技大學學報
국방과기대학학보
JOURNAL OF NATIONAL UNIVERSITY OF DEFENSE TECHNOLOGY
2014年
3期
111-115
,共5页
情感分析%情感词典%HowNet%语义关系
情感分析%情感詞典%HowNet%語義關繫
정감분석%정감사전%HowNet%어의관계
sentiment analysis%sentiment lexicon%HowNet%semantic relation
构建英文情感词典研究相对成熟,形成了丰富可靠的词典资源。而针对中文的研究时间短,中文情感分析词典资源较少。借鉴现有可靠的英文词典资源,提出了基于语义关系的情感词典自动构建算法,算法先从HowNet的概念中进行中文义原和词语抽取及语义分析,再利用HowNet概念中DEF中英文属性值,在英文情感词典SentWordNet中进行义原和词语情感值查询,最后根据词语和义原之间的语义关系进行词语的情感值计算。算法直接利用现有的英文情感词典,无须人工标注,生成的情感词典记录了词语的语义关系、情感极性值等多种信息,弥补了现有词典的不足。评测实验结果表明,根据算法实现的情感词典相比其他词典在准确率接近的情况下,召回率和F值最高,取得了较好的评测性能。
構建英文情感詞典研究相對成熟,形成瞭豐富可靠的詞典資源。而針對中文的研究時間短,中文情感分析詞典資源較少。藉鑒現有可靠的英文詞典資源,提齣瞭基于語義關繫的情感詞典自動構建算法,算法先從HowNet的概唸中進行中文義原和詞語抽取及語義分析,再利用HowNet概唸中DEF中英文屬性值,在英文情感詞典SentWordNet中進行義原和詞語情感值查詢,最後根據詞語和義原之間的語義關繫進行詞語的情感值計算。算法直接利用現有的英文情感詞典,無鬚人工標註,生成的情感詞典記錄瞭詞語的語義關繫、情感極性值等多種信息,瀰補瞭現有詞典的不足。評測實驗結果錶明,根據算法實現的情感詞典相比其他詞典在準確率接近的情況下,召迴率和F值最高,取得瞭較好的評測性能。
구건영문정감사전연구상대성숙,형성료봉부가고적사전자원。이침대중문적연구시간단,중문정감분석사전자원교소。차감현유가고적영문사전자원,제출료기우어의관계적정감사전자동구건산법,산법선종HowNet적개념중진행중문의원화사어추취급어의분석,재이용HowNet개념중DEF중영문속성치,재영문정감사전SentWordNet중진행의원화사어정감치사순,최후근거사어화의원지간적어의관계진행사어적정감치계산。산법직접이용현유적영문정감사전,무수인공표주,생성적정감사전기록료사어적어의관계、정감겁성치등다충신식,미보료현유사전적불족。평측실험결과표명,근거산법실현적정감사전상비기타사전재준학솔접근적정황하,소회솔화F치최고,취득료교호적평측성능。
Researches on constructing English sentiment lexicon is relatively mature,and there are abundant and reliable lexical resources. Whereas for Chinese studies,the research history is short,and there are only a few Chinese sentiment lexicon resources.With reliable English sentiment lexicon as reference,an automatic constructing approach was proposed,based on semantic relationships.Firstly the Chinese sememe and words were extracted from the defination of concepts in HowNet and the semantic analysis was carried out upon them;secondly the sentimental value of each sememe and word was retrieved from the English sentiment lexicon SentiWordNet according to the DEF attributes of concepts in HowNet, and the final sentimental value of each word was calculated on the semantic relations of the sememe and words.The ready English lexicon was used without manual labeling in the method,and diverse information of words was recorded in the final lexicon,including semantic relations and sentimental values,which remedy the lack of other lexicons.The experimental results show that the resulted sentiment lexicon can achieve better performance in the recall and F value measurements under the condition of approaching other lexicons on the precision measurements.