Recognizing Sentence Emotions Based on Polynomial Kernel Method Using Ren-CECps
Emotion recogonition on text has wide applications. In this study we propose a method of emotion recognition at sentence level based on a relative large emotion annotation corpus (Ren-CECps). From this corpus, we get the emotion lexicons for the eight basic emotions (expect, joy, love, surprise, anxiety, sorrow, angry and hate). Statistics show that the emotion lexicons derived from Ren-CECps are used more often in real use of language for emotional expressions than HOWNET sentimental lexicons. Kernel methods are state-of-the-art for solving machine learning problems. Polynomial kernel (PK) method is used to compute the similarities between sentences and the eight emotion lexicons. Then the experiential knowledge derived from Ren-CECps is used to recognize whether the eight emotion categories are present in a sentence. This method obtain 62.7% F-measure.
Emotion recognition polynomial kernel Ren-CECps affective computing
Changqin Quan Fuji Ren
Institute of Technology and Science The University of Tokushima 2-1 Minamijosanjima, Tokushima city, Japan
国际会议
大连
英文
1-7
2009-09-24（万方平台首次上网日期，不代表论文的发表时间）