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Data Analysis and Knowledge Discovery  2017, Vol. 1 Issue (12): 74-83    DOI: 10.11925/infotech.2096-3467.2017.0866
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Identifying Useful Online Reviews with Semantic Feature Extraction
Zhang Yanfeng(), Li He, Peng Lihui, Hou Litie
School of Management, Jilin University, Changchun 130022, China
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Abstract  

[Objective] We propose a model to identify useful online Chinese reviews, which helps consumers make purchasing decisions. [Methods] First, we calculated six attributes affecting the usefulness of online reviews based on their form and content characteristics. Then, we constructed a usefulness evaluation system with the weighted grey relational degree analysis method. Finally, we created a model to retrieve useful online reviews with k-means clustering method. [Results] We examined the effectiveness of our model with online reviews from Amazon.com. The recall, precision and F values showed that our method could effectively identify the useful online reviews, and classify the polarity ones. [Limitations] The samples, metrics and e-commerce platforms could be further improved. [Conclusions] The proposed method could rank and classify online reviews accurately and reliably.
Key words： Weighted Grey Relational Degree      Online Reviews      Classification Model      Usefulness     
Received: 28 August 2017      Published: 29 December 2017
ZTFLH:  G253 G202  
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Yanfeng Zhang
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Cite this article:

Zhang Yanfeng,Li He,Peng Lihui,Hou Litie. Identifying Useful Online Reviews with Semantic Feature Extraction. Data Analysis and Knowledge Discovery, 2017, 1(12): 74-83.

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https://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/10.11925/infotech.2096-3467.2017.0866     OR     https://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/Y2017/V1/I12/74

属性 权重 产品词汇
特殊术语 0.10 商品指代(手机、宝贝等)、品牌名称(苹果、三星等)、专有名词(翻新机、品牌机等)
产品功能 0.25 商务功能、拍照功能、数据应用功能、音乐功能、游戏功能、GPS导航功能
产品性能 0.30 手机反应速度、扩展性、通信质量、电池
续航能力、信号收发能力
外观形态 0.15 材料、键盘类型、输入方式、机身大小、
设计、颜色
技术指标 0.20 CPU配置、网络制式、触屏方式、分辨率、尺寸、内存、存储扩展
属性 权重 示例
情感词 ω1 完美、爱、喜欢、还行、无感、还好、不好、信赖、多、满意、推荐、愉快、一般……(1 800个)
特殊关键词 ω2 啊、呢、吗、嘛、吖……(16个)
特殊符号 ω2 :)、:-)、^O^ 、O(∩_∩)O、\(^o^)/……(84个)
特殊句式 ω2 反问句、疑问句(统计?号), 感叹句(统计!号)
属性 程度 修饰词
评论修饰词 极(E) 极、过、至、顶、最、最为、无比、极度、极其、极为、极端、万分、过分、分外、过于、至为
高(H) 太、挺、满、越、更、忒、特、多、够、蛮、殊、愈、甚、更、尤其、大为、越发、多么、深为、备加、十分、相当、特别、非常、格外、越加
中(M) 较、很、比较、较为、不太、不大、不很
低(L) 稍、略、多少、有点、略为、稍许、稍微、些许
重要程度 说明 标度f(x, y)
属性x较y同等重要 x、y对总目标的贡献相同 1
属性x较y稍微重要 x的贡献稍大于y 3
属性x较y明显重要 x的贡献明显大于y 5
属性x较y特别重要 x的贡献特别明显大于y 7
属性x较y极端重要 x的贡献以压倒优势大于y 9
属性x较y介于各等
级之间		 相邻两判断的折中 2,4,6,8
指标
样本		 有用
投票		 图片
数量		 时效
性		 产品
属性词		 情感
强度		 修饰
词
1 0.72 0 15 4.56 6.50 3.90
2 1.14 2 19 6.62 15.30 4.50
3 0.96 2 21 6.86 14.30 5.20
… … … … … … …
48 1.64 6 25 7.35 15.90 6.40
49 0.66 0 11 4.87 7.90 4.20
50 1.18 4 26 6.25 12.70 5.40
指标
样本		 有用
投票		 图片
数量		 时效
性		 产品
属性词		 情感
强度		 修饰
词		 关联
度
1 0.667 0.512 0.333 0.388 1.000 0.887 0.691
2 0.610 0.333 1.000 0.667 0.890 0.667 0.725
3 1.000 0.750 0.889 0.780 0.500 0.667 0.723
… … … … … … … …
48 0.667 0.889 0.623 0.650 1.000 0.650 0.755
49 0.649 1.000 0.645 0.667 0.333 1.000 0.671
50 0.466 0.510 1.000 0.667 0.733 0.889 0.725
聚类结果 等级 中心点 样本编号(按有用性排序)
第1类(15个) 1 0.74783 48 32 24 37 18 12 42 28 44 7 4
15 10 22 34
第2类(14个) 2 0.72618 25 47 39 20 30 43 14 2 50 23
19 3 35 9
第3类(11个) 3 0.69391 13 45 16 6 21 31 1 40 27 29 38
第4类(10个) 4 0.66844 11 26 49 8 17 33 36 41 5 46
聚类结果 Precision Recall F值
第1类 93.33%(14/15) 87.50%(14/16) 90.31%
第2类 78.57%(11/14) 84.62%(11/13) 81.48%
第3类 72.73%(9/12) 81.82%(9/11) 77.01%
第4类 100.00%(9/9) 90.00%(9/10) 94.74%
平均 86.16% 85.99% 86.07%
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