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Data Analysis and Knowledge Discovery  2018, Vol. 2 Issue (8): 60-68    DOI: 10.11925/infotech.2096-3467.2017.1043
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Sentiment Mining of Online Product Reviews Based on Domain Ontology
He Youshi, He Shufang()
School of Management, Jiangsu University, Zhenjiang 212013, China
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Abstract  

[Objective] This paper studies the relationship between the product attributes and the emotional attitudes of consumers, aiming to optimize the sentiment analysis on consumer reviews. [Methods] First, we constructed the product domain ontology to extract the needed attributes. Then, we built the product attribute hierarchy model, which combined the collocation weight of emotional words with attribute words to identify implicit attributes. Third, we created a dictionary to calculate the emotional orientation of product attributes at all levels for the sentiment analysis. [Results] We examined the proposed model with online reviews of smart phones and found it improved the accuracy of emotion classification. [Limitations] The construction of ontology needs to be further improved. [Conclusions] The proposed method could effectively identify the logical relationship among attributes, which improve the performance of sentiment analysis in real world cases.

Key wordsDomain Ontology      Product Feature      Multilevel      Fine-grained Emotional Orientation     
Received: 20 October 2017      Published: 08 September 2018
ZTFLH:  TP391  

Cite this article:

He Youshi,He Shufang. Sentiment Mining of Online Product Reviews Based on Domain Ontology. Data Analysis and Knowledge Discovery, 2018, 2(8): 60-68.

URL:

https://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/10.11925/infotech.2096-3467.2017.1043     OR     https://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/Y2018/V2/I8/60

正向情感评价词(+1) 负向情感评价词(-1)
清晰 赞 快 明显 有趣 多
耐用 舒服 酷 震撼 好
好玩 实惠 好用
模糊 慢 卡 漏光 简陋 差
发烫 死机 耗电 瑕疵 划痕
断流 跑电 缝隙
正向情感评价词(+1) 负向情感评价词(-1)
配置高 科技含量重
清晰度高 性价比高
操作简单 功能强 耗电低
价格高 重量重 做工简单
功能简单噪音强 配置低
包装低
情感强度值 程度副词
0.25 稍微 些许 略 略微 多少 有点 有些有点儿
0.75 较 较为 比较 不大 不太 不很
1.25 很 更 更加 更为 越 越发 备加 愈 愈加 愈发 越 格外 太 挺 忒 非常 特别 相当 十分 甚 颇 甚为 颇为 满 蛮 够 多么 真 特大 尤其
1.75 最 最为 极 极为 极其 极度 分外 要命
否定词(-1)
不、非、别、甭、不必、不曾、不要、没、没有、不用、
何必、何须、何曾、何尝、空、白、不是、徒、徒然、
无能、未、未曾、未尝、无需、毋庸、勿、否
情感要素 处理规则
图片 若采用图片的形式来辅助评论文本的表达, 则对文本所表达属性的情感倾向进行调整, 将总的情感倾向乘以1.25倍
符号 ? 根据语义情况具体分析, 有可能语义不变, 有可能反向改变
“” 若情感词带有双引号, 则情感极性反向处理
若评论文本中带有感叹号, 则加重所表达的情感倾向, 加重程度与图片一致, 将总的情感倾向乘以1.25倍
隐式句子 映射属性词 搭配权重
用着很流畅, 不愧是835的处理器 操作系统 (操作系统流畅, 0.832)
很清晰, 效果不错 屏幕 (屏幕清晰, 0.623)
有点小贵, 感觉不值 价格 (价格贵, 1)
买的4+64的, 看起来很漂亮 外观 (外观漂亮, 0.72)
还行, 应该是新机, 不卡 操作系统 (操作系统卡, 0.728)
实验方法 查准率 查全率 F值
本文方法 89.4% 86.9% 88.1%
产品属性类的方法 80.6% 76.1% 78.3%
[1] 潘宇, 林鸿飞. 基于语义极性分析的餐馆评论挖掘[J]. 计算机工程, 2008, 34(17): 208-210.
doi: 10.3969/j.issn.1000-3428.2008.17.074
[1] (Pan Yu, Lin Hongfei.Restaurant Reviews Mining Based on Semantic Polarity Analysis[J]. Computer Engineering, 2008, 34(17): 208-210.)
doi: 10.3969/j.issn.1000-3428.2008.17.074
[2] 尹裴, 王洪伟. 面向产品特征的中文在线评论情感分类: 以本体建模为方法[J]. 系统管理学报, 2016, 25(1): 103-114.
[2] (Yin Pei, Wang Hongwei.Sentiment Classification for Chinese Online Reviews at Product Feature Level Through Domain Ontology Method[J]. Journal of Systems and Management, 2016, 25(1): 103-114.)
[3] Yu H, Hatzivassiloglou V.Towards Answering Opinion Questions: Separating Facts from Opinions and Identifying the Polarity of Opinion Sentences[C]//Proceedings of the 2003 Conference on Empirical Methods in Natural Language Processing. 2003: 129-136.
[4] Pang B, Lee L.Opinion Mining and Sentiment Analysis[J]. Foundations and Trends in Information Retrieval, 2008, 2(1-2): 1-135.
doi: 10.1561/1500000011
[5] Turney P D.Thumbs up or Thumbs down?: Semantic Orientation Applied to Unsupervised Classification of Reviews[C]//Proceedings of the 40th Annual Meeting on Association for Computational Linguistics. Stroudsburg, PA, USA: Association for Computational Linguistics, 2002: 417-424.
[6] He R, Gonzalez H.Numerical Synthesis of Pontryagin Optimal Control Minimizers Using Sampling-Based Methods[C]//Proceedings of the IEEE 56th Annual Conference on Decision and Control (CDC). Melbourne, Australia: IEEE CDC, 2017:733-738.
[7] Meena A, Prabhakar T V.Sentence Level Sentiment Analysis in the Presence of Conjuncts Using Linguistic Analysis[C]// Proceedings of the European Conference on Information Retrieval. 2007: 573-580.
[8] 张成功, 刘培玉, 朱振方, 等. 一种基于极性词典的情感分析方法[J]. 山东大学学报: 理学版, 2012, 47(3): 47-50.
[8] (Zhang Chenggong, Liu Peiyu, Zhu Zhenfang, et al.A Sentiment Analysis Method Based on a Polarity Lexion[J]. Journal of Shandong University: Natural Science, 2012, 47(3): 47-50.)
[9] Fu X, Liu G, Guo Y, et al.Multi-aspect Sentiment Analysis for Chinese Online Social Reviews Based on Topic Modeling and HowNet Lexicon[J]. Knowledge Based Systems, 2013, 37: 186-195.
doi: 10.1016/j.knosys.2012.08.003
[10] Kim S M, Hovy E. Extracting Opinions, Opinion Holders,Topics Expressed in Online News Media Text[C]// Proceedings of the Workshop on Sentiment & Subjectivity in Text at the International Conference on Computational Linguistics/the Annual Meeting of the Association for Computational Linguistics Sentiment and Subject. 2006: 101-108.
[11] Hai Z, Chang K, Kim J.Implicit Feature Identification via Co-occurrence Association Rule Mining[C]//Proceedings of the 12th International Conference on Intelligent Text Processing and Computational Linguistics. Berlin: Springer-Verlag, 2011: 393-404.
[12] 朱嫣岚, 闵锦, 周雅倩, 等. 基于HowNet的词汇语义倾向计算[J]. 中文信息学报, 2006, 20(1): 14-20.
doi: 10.3969/j.issn.1003-0077.2006.01.003
[12] (Zhu Yanlan, Min Jin, Zhou Yaqian, et al.Semantic Orientation Computing Based on HowNet[J]. Journal of Chinese Information Processing, 2006, 20(1): 14-20.)
doi: 10.3969/j.issn.1003-0077.2006.01.003
[13] Xu H, Zhang F, Wang W.Implicit Feature Identification in Chinese Reviews Using Explicit Topic Mining Model[J]. Knowledge Based Systems. 2015, 76: 166-175.
doi: 10.1016/j.knosys.2014.12.012
[14] Carenini G, Ng R T, Zwart E.Extracting Knowledge from Evaluative Text[C]//Proceedings of the 3rd International Conference on Knowledge Capture. Edmonton: ACM, 2005: 11-18.
[15] Yu J X, Zha Z J, Wang M, et al.Domain-Assisted Product Aspect Hierarchy Generation: Towards Hierarchical Organization of Unstructured Consumer Reviews[C]// Proceedings of 2011 Conference on Empirical Methods in Natural Language Processing. Edinburgh: ACL, 2011: 140-150.
[16] Yin P, Wang H, Guo K.Feature-Opinion Pair Identification of Product Reviews in Chinese: A Domain Ontology Modeling Method[J]. New Review of Hypermedia and Multimedia, 2013, 19(1): 3-24.
doi: 10.1080/13614568.2013.766266
[17] 唐晓波, 兰玉婷. 基于特征本体的微博产品评论情感分析[J]. 图书情报工作, 2016, 60(16): 121-127.
[17] (Tang Xiaobo, Lan Yuting.Sentiment Analysis of Microblog Product Reviews Based on Feature Ontology[J]. Library and Information Service, 2016, 60(16): 121-127.)
[18] 杜嘉忠, 徐健, 刘颖. 网络商品评论的特征-情感词本体构建与情感分析方法研究[J]. 现代图书情报技术, 2014(5): 74-82.
[18] (Du Jiazhong, Xu Jian, Liu Ying.Research on Construction of Feature-Sentiment Ontology and Sentiment Analysis[J]. New Technology of Library and Information Service, 2014(5): 74-82.)
[19] 李金海, 何有世, 马云蕾, 等. 基于在线评论信息挖掘的动态用户偏好模型构建[J]. 情报杂志, 2016, 35(9): 192-198.
[19] (Li Jinhai, He Youshi, Ma Yunlei, et al.Building Dynamic User Preference Model Based on Information Mining of Online Reviews[J]. Journal of Intelligence, 2016, 35(9): 192-198.)
[20] Gruber T R.Toward Principles for the Design of Ontologies Used for Knowledge Sharing[J]. International Journal of Human-Computer Studies, 1995, 43(5-6): 907-928.
doi: 10.1006/ijhc.1995.1081
[21] 董丽丽, 赵繁荣, 张翔. 基于领域本体、情感词典的商品评论倾向性分析[J]. 计算机应用与软件, 2014, 31(12): 104-108.
doi: 10.3969/j.issn.1000-386x.2014.12.024
[21] (Dong Lili, Zhao Fanrong, Zhang Xiang.Analysing Propensity of Product Reviews Based on Domain Ontology and Sentiment Lexicon[J]. Computer Applications and Software, 2014, 31(12): 104-108.)
doi: 10.3969/j.issn.1000-386x.2014.12.024
[22] 尹裴, 王洪伟, 郭恺强. 中文产品评论的“特征观点对”识别: 基于领域本体的建模方法[J]. 系统工程, 2013, 31(1): 68-77.
[22] (Yin Pei, Wang Hongwei, Guo Kaiqiang.Feature-Opinion Pair Identification in Chinese Online Reviews Based on Domain Ontology Modeling Method[J]. Systems Engineering, 2013, 31(1): 68-77.)
[23] Protégé [EB /OL]. [2010-12-12]..
[24] 宋园园, 余建坤. 一种基于领域知识的特征提取算法[J].云南民族大学学报: 自然科学版, 2017, 26(3): 252-257.
[24] (Song Yuanyuan, Yu Jiankun.A Feature Extraction Algorithm Based on Domain Knowledge[J]. Journal of Yunnan Minzu University: Natural Sciences Edition, 2017, 26(3): 252-257.)
[25] 杨燕霞. 基于本体的旅游网络评论情感分析与预警系统[J]. 计算机与数字工程, 2016, 44(4): 649-652.
doi: 10.3969/j.issn.1672-9722.2016.04.020
[25] (Yang Yanxia.Tourism Network Comments Sentiment Analysis and Pre-warning System Based on Ontology[J]. Computer and Digital Engineering, 2016, 44(4): 649-652.)
doi: 10.3969/j.issn.1672-9722.2016.04.020
[26] 张莉, 许鑫. 产品评论中的隐式属性抽取研究[J]. 现代图书情报技术, 2015(12): 42-47.
[26] (Zhang Li, Xu Xin.Implicit Feature Identification in Product Reviews[J]. New Technology of Library and Information Service, 2015(12): 42-47.)
[27] 赵志滨, 刘欢, 姚兰, 等. 中文产品评论的维度挖掘及情感分析技术研究[J]. 计算机科学与探索, 2018, 12(3): 341-349.
[27] (Zhao Zhibin, Liu Huan, Yao Lan, et al.Research on Dimension Mining and Sentiment Analysis for Chinese Product Comments[J]. Journal of Frontiers of Computer Science and Technology, 2018, 12(3): 341-349.)
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[7] Yan Shiyan, Wang Shengqing, Luo Yunchuan, Huang Haojun. An Ontology Collaborative Construction Model Based on FCA in Cloud Computing Environment[J]. 现代图书情报技术, 2014, 30(3): 49-56.
[8] Yao Xiaona, Zhu Zhongming, Wang Sili. Research on Automatic Semantic Annotation for Geosciences[J]. 现代图书情报技术, 2013, (4): 48-53.
[9] Xu Xin, Guo Jinlong. Construction of Subject Knowledge Base——Taking the Domain of Chinese Cuisine Culture as an Example[J]. 现代图书情报技术, 2013, (12): 2-9.
[10] Guo Jinlong, Hong Yunjia, Xu Xin. Construction and Application of Ontology in the Domain of Chinese Cuisine Culture[J]. 现代图书情报技术, 2013, (12): 10-18.
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[13] Wang Yong, Zhang Qin, Yang Xiaojie. Research on the Method of Extracting Features from Chinese Product Reviews on the Internet[J]. 现代图书情报技术, 2013, (12): 70-73.
[14] Tang Xiaobo, Xiao Lu. Research of Co-word Analysis Method of Combining Keywords Extension and Domain Ontology[J]. 现代图书情报技术, 2013, 29(11): 60-67.
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