Generating Aspect-based Extractive Opinion Summary: Drawing Inferences from Social Media Texts

被引：0
|
作者：
Piryani, Rajesh [1 ]
Gupta, Vedika [2 ]
Singh, Vivek Kumar [3 ]
机构：
[1] South Asian Univ, Dept Comp Sci, New Delhi, India
[2] Natl Inst Technol Delhi, Dept Comp Sci, Delhi, India
[3] Banaras Hindu Univ, Dept Comp Sci, Varanasi, Uttar Pradesh, India
来源：
COMPUTACION Y SISTEMAS | 2018年 / 22卷 / 01期
关键词：
Aspect-level sentiment analysis; laptop; polarity; sentiment summarization; big data;
D O I：
10.13053/CyS-22-1-2784
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
This paper presents an integrated framework to generate extractive aspect-based opinion summary from a large volume of free-form text reviews. The framework has three major components: (a) aspect identifier to determine the aspects in a given domain; (b) sentiment polarity detector for computing the sentiment polarity of opinion about an aspect; and (c) summary generator to generate opinion summary. The framework is evaluated on SemEval-2014 dataset and obtains better results than several other approaches.
引用
收藏
页码：83 / 91
页数：9
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