Aspect-Based Sentiment Analysis Using Tree Kernel Based Relation Extraction

被引：12
|
作者：
Thien Hai Nguyen [1 ]
Shirai, Kiyoaki [1 ]
机构：
[1] Japan Adv Inst Sci & Technol, Sch Informat Sci, Nomi, Ishikawa 9231292, Japan
来源：
COMPUTATIONAL LINGUISTICS AND INTELLIGENT TEXT PROCESSING (CICLING 2015), PT II | 2015年 / 9042卷
关键词：
Sentiment Analysis; Relation Extraction; Tree Kernel; Support Vector Machine;
D O I：
10.1007/978-3-319-18117-2_9
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
We present an application of kernel methods for extracting relation between an aspect of an entity and an opinion word from text. Two tree kernels based on the constituent tree and dependency tree were applied for aspect-opinion relation extraction. In addition, we developed a new kernel by combining these two tree kernels. We also proposed a new model for sentiment analysis on aspects. Our model can identify polarity of a given aspect based on the aspect-opinion relation extraction. It outperformed the model without relation extraction by 5.8% on accuracy and 4.6% on F-measure.
引用
收藏
页码：114 / 125
页数：12
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