Automatic affect recognition using natural language processing techniques and manually built affect lexicon

被引：0
|
作者：
Cho, Young Hwan [1 ]
Lee, Kong Joo [1 ]
机构：
[1] Chungnam Natl Univ, Fac Dept Informat & Commun Engn, Taejon, South Korea
来源：
IEICE TRANSACTIONS ON INFORMATION AND SYSTEMS | 2006年 / E89D卷 / 12期
关键词：
affect; affect recognition; affect lexicon; natural language processing techniques;
D O I：
10.1093/ietisy/e89-d.12.2964
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
In this paper, we present preliminary work on recognizing affect from a Korean textual document by using a manually built affect lexicon and adopting natural language processing tools. A manually built affect lexicon is constructed in order to be able to detect various emotional expressions, and its entries consist of emotion vectors. The natural language processing tools analyze an input document to enhance the accuracy of our affect recognizer. The performance of our affect recognizer is evaluated through automatic classification of song lyrics according to moods.
引用
收藏
页码：2964 / 2971
页数：8
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