Statistical Feature based Approach for Aspect Oriented Sentiment Analysis

被引：0

作者：

Shelke, Nilesh M. ^{[1
]}

Deshpande, Shrinivas ^{[2
]}

Thakare, Vilas ^{[3
]}

机构：

[1] SGB Amravati Univ, Amravati, MS, India

[2] HVPM, DCPE, Dept Comp Sci & Technol, Amravati, MS, India

[3] SGB Amravati Univ, Dept Comp Sci & Engn, Amravati, India

来源：

PROCEEDINGS OF THE 2017 INTERNATIONAL CONFERENCE ON INVENTIVE COMMUNICATION AND COMPUTATIONAL TECHNOLOGIES (ICICCT) | 2017年

关键词：

sentiment analysis; SentiWordNet; synset; sentiment score; POS Tagger;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

User generated data is tremendously increasing on the web. Many social networking sites are popular and powerful platforms for finding friends and people like to post comments. This data can be exploited for analyzing sentiments of the user. Feature extraction from text is crucial stage for sentiment analysis. This paper is intended to propose a simple method for feature extraction from text. Proposed method measures semantic relatedness /similarity from WordNet. Advantage of the proposed method is that it is domain independent. SentiWordNet 3.0 has been used for polarity classification. Average accuracy obtained for camera domain is 0.847 and restaurant domain is 90%.

引用

页码：376 / 381

页数：6

共 14 条

[1]

Agarwal Apoorv, 2016, S COL DAT AN NETW MA

[2]

[Anonymous], 2010, IEEE INTELL SYST

[3]

[Anonymous], 2016, P GLOB WORDNET C

[4] Mining Social Emotions from Affective Text [J].

Bao, Shenghua ;

Xu, Shengliang ;

Zhang, Li ;

Yan, Rong ;

Su, Zhong ;

Han, Dingyi ;

Yu, Yong .

IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING, 2012, 24 (09) :1658-1670

[5]

Cho Heeryon, 2016, INT C BIG DAT SMART, P102

[6]

Ghorashi S.H., 2012, INT J COMPUTER SCI I, V9, P29

[7]

Huang Wei-Jie, 2015, SOFT COMPUTING

[8]

Mahgoub Hany, 2008, INT J COMPUTATIONAL, V4, P1

[9]

NagaPrasad S., INT C COMP COMM CONV, P58

[10]

Pawar AB, 2016, STUD COMPUT INTELL, V639, P25, DOI 10.1007/978-3-319-30319-2_2

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