Please wait a minute...
New Technology of Library and Information Service  2014, Vol. 30 Issue (4): 65-70    DOI: 10.11925/infotech.1003-3513.2014.04.10
Current Issue | Archive | Adv Search |
Mining Customer Focus Features from Product Reviews Oriented Supply Chain
Hao Mei, Wang Daoping
Dongling School of Economics and Management, University of Science and Technology Beijing, Beijing 100083, China
Download:
Export: BibTeX | EndNote (RIS)      
Abstract  

[Objective] This paper proposes a customer focus feature mining method oriented supply chain. [Methods] The association rule mining is improved by adding data preprocessing, which includes product evaluation conception tree, product evaluation feature database and MA_Apriori algorithm. Based on the data of tablet PC of Jingdong Mall, the data experiment mines the customer focus features in Weka. [Results] The experiments show that the recall radio of new method is 90.5%, but the association rule method is 71.4%. In addition, it can get the hierarchical and standardized products features. [Limitations] Considering the accuracy of word segmentation, the user dictionary of segmentation system needs to be replenished by adding the product professional vocabulary. [Conclusions] This paper can help each enterprise select the product evaluation conception hierarchies flexibly, then improve the qualities of products and service.

Key wordsProduct evaluation conception tree      Customer focus feature      Association rule      Data mining      Supply chain     
Received: 28 August 2013      Published: 19 May 2014
:  TP391  

Cite this article:

Hao Mei, Wang Daoping. Mining Customer Focus Features from Product Reviews Oriented Supply Chain. New Technology of Library and Information Service, 2014, 30(4): 65-70.

URL:

https://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/10.11925/infotech.1003-3513.2014.04.10     OR     https://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/Y2014/V30/I4/65

[1] McKinsey.2011年度中国消费者调查报告[R].2011:22-34.(McKinsey.Chinese Consumer Survey Report for 2011[R].2011:22-34.)
[2] Popescu A M,Etzioni O.Extracting Product Features and Opinions from Reviews[C].In:Proceedings of the Conference on Human Language Technology and Empirical Methods in Natural Language Processing.Stroudsburg,PA,USA:Association for Computational Linguistics,2005:339-346.
[3] Kobayashi N,Inui K,Matsumoto Y,et al.Collecting Evaluative Expressions for Opinion Extraction[C].In:Proceedings of the 1st International Joint Conference on Natural Language Processing.2004:596-605.
[4] 姚天昉,程希文,徐飞玉,等.文本意见挖掘综述[J].中文信息学报,2008,22(3):71-80.(Yao Tianfang,Cheng Xiwen,Xu Feiyu,et al.A Survey of Opinion Mining for Texts[J].Journal of Chinese Information Processing,2008,22(3):71-80.)
[5] Zhuang L,Jing F,Zhu X Y.Movie Review Mining and Summarization[C].In:Proceedings of the 15th ACM International Conference on Information and Knowledge Management.New York:ACM,2006:43-50.
[6] 伍星,何中市,黄永文.产品评论挖掘研究综述[J].计算机工程与应用,2008,44(36):37-40.(Wu Xing,He Zhongshi,Huang Yongwen.Product Review Mining:A Survey[J].Computer Engineering and Applications,2008,44(36):37-40.)
[7] Hu M,Liu B.Mining Opinion Features in Customer Reviews[C].In:Proceedings of the 19th National Conference on Artificial Intelligence.AAAI Press,2004:755-760.
[8] Agrawal R,Srikant R.Fast Algorithms for Mining Association Rules in Large Databases[C].In:Proceeding of the 20th International Conference on Very Large Data Bases,Santiago de Chile.1994:487-499.
[9] Liu B,Hsu W,Ma Y.Integrating Classification and Association Rule Mining[C].In:Proceedings of the KDD-98.1998:80-86.
[10] Popescu A M,Etzioni O.Extracting Product Features and Opinions from Reviews[C].In:Proceedings of the Conference on Human Language Technology and Empirical Methods in Natural Language Processing,Vancouver,Canada.2005:339-346.
[11] 李实,叶强,李一军,等.中文网络客户评论的产品特征挖掘方法研究[J].管理科学学报,2009,12(2):142-151.(Li Shi,Ye Qiang,Li Yijun,et al.Mining Features of Products from Chinese Customer Online Reviews[J].Journal of Management Sciences in China,2009,12(2):142-151.)
[12] Wang B,Wang H.Bootstrapping both Product Properties and Opinion Words from Chinese Reviews with Cross-training[C].In:Proceedings of the IEEE/WIC/ACM International Conference on Web Intelligence.Washington,DC,USA:IEEE Computer Society,2007:259-262.
[13] Zheng Y,Ye L,Wu G,et al.Extracting Product Features from Chinese Customer Reviews[C].In:Proceedings of the 3rd International Conference on Intelligent System and Knowledge Engineering.Washington:IEEE Computer Society,2008:285-290.
[14] 肖娟,叶枫.基于概念层次树的数据挖掘算法及应用研究[J].计算机应用研究,2005,22(3):61-64.(Xiao Juan,Ye Feng.Research on Data Mining Algorithm Based on Conception Hierarchy Tree and Its Application[J].Application Research of Computers,2005,22(3):61-64.)
[15] 王圣广,马士华.论供应链驱动模式[J].中国软科学,1999(4):34-36.(Wang Shengguang,Ma Shihua.Research on Supply Chain Driven Mode[J].China Soft Science,1999(4):34-36.)
[16] Maedche A,Motik B,Stojanovic L,et al.An Infrastructure for Searching,Reusing and Evolving Distributed Ontologies[C].In:Proceedings of the 12th International Conference on World Wide Web.2003:439-448.
[17] 周立柱,林玲.聚焦爬虫技术研究综述[J].计算机应用,2005,25(9):1965-1969.(Zhou Lizhu,Lin Ling.Survey on the Research of Focused Crawling Technique[J].Computer Applications,2005,25(9):1965-1969.)
[18] Hu M,Liu B.Mining and Summarizing Customer Reviews[C].In:Proceedings of the 10th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining,Seattle,USA.2004:168-177.

[1] Xie Wang, Wang Lizhen, Chen Hongmei, Zeng Lanqing. Identifying Relationship Between Pollution Sources and Cancer Cases with Spatial Ordered Pair Patterns[J]. 数据分析与知识发现, 2021, 5(2): 14-31.
[2] Li Tiejun,Yan Duanwu,Yang Xiongfei. Recommending Microblogs Based on Emotion-Weighted Association Rules[J]. 数据分析与知识发现, 2020, 4(4): 27-33.
[3] Mingxuan Huang,Shoudong Lu,Hui Xu. Cross-Language Information Retrieval Based on Weighted Association Patterns and Rule Consequent Expansion[J]. 数据分析与知识发现, 2019, 3(9): 77-87.
[4] Yong Zhang,Shuqing Li,Yongshang Cheng. Mining Algorithm for Weighted Association Rules Based on Frequency Effective Length[J]. 数据分析与知识发现, 2019, 3(7): 85-93.
[5] Quan Lu,Anqi Zhu,Jiyue Zhang,Jing Chen. Research on User Information Requirement in Chinese Network Health Community: Taking Tumor-forum Data of Qiuyi as an Example[J]. 数据分析与知识发现, 2019, 3(4): 22-32.
[6] Dongmei Mu,Hui Fa,Ping Wang,Jing Sun. Research on Disease Risk Factors on Structural Equation Model[J]. 数据分析与知识发现, 2019, 3(4): 80-89.
[7] He Yue,Feng Yue,Zhao Shupeng,Ma Yufeng. Recommending Contents Based on Zhihu Q&A Community: Case Study of Logistics Topics[J]. 数据分析与知识发现, 2018, 2(9): 42-49.
[8] Meng Hu,Liang Xiaobei,Yang Yixiong,Li Min. Evaluating and Optimizing Supply Chains with LMBP Algorithm[J]. 数据分析与知识发现, 2018, 2(11): 37-45.
[9] Li Yongnan. Using Bayes Theory to Classify Counter Terrorism Intelligence[J]. 数据分析与知识发现, 2018, 2(10): 9-14.
[10] Mu Dongmei,Wang Ping,Zhao Danning. Reducing Data Dimension of Electronic Medical Records: An Empirical Study[J]. 数据分析与知识发现, 2018, 2(1): 88-98.
[11] He Yue,Wang Aixin,Feng Yue,Wang Li. Optimizing Layouts of Outpatient Pharmacy Based on Association Rules[J]. 数据分析与知识发现, 2018, 2(1): 99-108.
[12] Hu Zhongyi,Wang Chaoqun,Wu Jiang. Identifying Phishing Websites with Multiple Online Data Sources[J]. 数据分析与知识发现, 2017, 1(6): 47-55.
[13] Jiang Siwei,Xie Zhenping,Chen Meijie,Cai Ming. Self-Explainable Reduction Method for Mixed Feature Data Modeling[J]. 数据分析与知识发现, 2017, 1(12): 92-100.
[14] Wei Xing,Hu Dehua,Yi Minhan,Zhu Qizhen,Zhu Wenjie. Extracting Disease-Gene-Drug Correlations Based on Data Cube[J]. 数据分析与知识发现, 2017, 1(10): 94-104.
[15] Huang Mingxuan. Cross Language Information Retrieval Model Based on Matrix-weighted Association Patterns Mining[J]. 数据分析与知识发现, 2017, 1(1): 26-36.
  Copyright © 2016 Data Analysis and Knowledge Discovery   Tel/Fax:(010)82626611-6626,82624938   E-mail:jishu@mail.las.ac.cn