[1]YU Zhigang,CHENG Siyuan,YANG Xuerong,et al.Product improvement demand identification incorporating topology and online comment mining[J].CAAI Transactions on Intelligent Systems,2023,18(5):1047-1059.[doi:10.11992/tis.202208052]
Copy
Product improvement demand identification incorporating topology and online comment mining
CAAI Transactions on Intelligent Systems[ISSN 1673-4785/CN 23-1538/TP] Volume:
18
Number of periods:
2023 5
Page number:
1047-1059
Column:
学术论文—机器学习
Public date:
2023-09-05
- Title:
- Product improvement demand identification incorporating topology and online comment mining
- Keywords:
- topology; online comment; matter-element model; affair-element model; emotion inclination pointwise mutual information algorithm; correlative network; implication system; demand identification
- CLC:
- TP18
- DOI:
- 10.11992/tis.202208052
- Abstract:
- Formal and organized mining and clarifying of different categories of product improvement demands from online comments are necessary for the product improvement process. On considering the multilevel and multifeature nature of product design information, a topological analysis method based on a matter-element model used for hierarchical representation of online review product design information and identification of product improvement demands was proposed. PYLDAvis interactive visualization library was used to extract product elements from online comments, and the product elements were then divided into three levels, namely entity, function, and attribute. In addition, the matter-element model was used for hierarchical expression. The emotion inclination pointwise mutual information algorithm was combined to calculate the evaluation value of user opinions at all levels, and an affair–element model was used to express the user’s demand for the object features with low evaluation value. The correlation network analysis method was used to determine the relationship between defective matter elements, and the implication system analysis method was used to determine the realization of the product improvement demand. The case study took the online reviews of a health pot as an example, the user’s improvement demands for the product were found by mining online reviews, and means to achieve the demands were identified. A product improvement demand identification method incorporating topology and online comment mining can realize the hierarchical expression of user demands and clarify product improvement design information in a formalized and organized manner, providing a scientific basis and effective methods for identifying the improvement paths of products.
- References:
-
[1] LAI Xinjun, ZHANG Qixiang, CHEN Qingxin, et al. The analytics of product-design requirements using dynamic Internet data: application to Chinese smartphone market[J]. International journal of production research, 2019, 57(18): 5660-5684.
[2] 冯立杰, 关柯楠, 王金凤. 基于在线评论考虑潜在用户需求的产品创新方案识别研究[J]. 情报理论与实践, 2022, 45(6): 129-137
FENG Lijie, GUAN Kenan, WANG Jinfeng. Research on product innovation scheme identification considering potential user needs based on online comments[J]. Information studies:theory & application, 2022, 45(6): 129-137
[3] 王慧. 基于特征提取和情感分析的用户需求挖掘研究[D]. 杭州: 浙江理工大学, 2019: 5?17.
WANG Hui. Research on user demand mining based on feature extraction and emotion analysis[D]. Hangzhou: Zhejiang Sci-Tech University, 2019: 5?17.
[4] 徐凯. 基于产品特征的用户评论情感倾向分析研究[D]. 合肥: 合肥工业大学, 2015: 8?11.
XU Kai. Research on sentiment orientation analysis of user reviews based on product features[D]. Hefei: Hefei University of Technology, 2015: 8?11.
[5] 李贺, 曹阳, 沈旺, 等. 基于LDA主题识别与Kano模型分析的用户需求研究[J]. 情报科学, 2021, 39(8): 3-11,36
LI He, CAO Yang, SHEN Wang, et al. User demand based on LDA subject identification and Kano model analysis[J]. Information science, 2021, 39(8): 3-11,36
[6] DAY M Y, TENG H C. A study of deep learning to sentiment analysis on word of mouth of smart bracelet[C]//Proceedings of the 2017 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining. New York: ACM, 2017: 763?770.
[7] YEH C T, CHEN Muchen. Applying Kansei Engineering and data mining to design door-to-door delivery service[J]. Computers & industrial engineering, 2018, 120: 401-417.
[8] 李江泳, 张伟. 在线评论数据挖掘视角下的产品改良设计研究[J]. 包装工程, 2021, 42(6): 135-141
LI Jiangyong, ZHANG Wei. Product improvement design from the perspective of online comment data mining[J]. Packaging engineering, 2021, 42(6): 135-141
[9] 萧筝. 客户需求信息处理理论和方法研究[D]. 武汉: 武汉理工大学, 2013: 5?20.
XIAO Zheng. Research on theories and methods of customer requirement information processing[D]. Wuhan: Wuhan University of Technology, 2013: 5?20.
[10] 赵云彦, 韩冬楠, 尤立思, 等. 基于用户需求层次分析的女性安全防护产品设计研究[J]. 包装工程, 2021, 42(16): 120-126
ZHAO Yunyan, HAN Dongnan, YOU Lisi, et al. The design of women’s safety protection products based on the level of users’ demand[J]. Packaging engineering, 2021, 42(16): 120-126
[11] 纪雪, 高琦, 李先飞, 等. 考虑产品属性层次性的评论挖掘及需求获取方法[J]. 计算机集成制造系统, 2020, 26(3): 747-759
JI Xue, GAO Qi, LI Xianfei, et al. Reviews mining and requirements elicitation methodology considering product attributes’ hierarchy[J]. Computer integrated manufacturing systems, 2020, 26(3): 747-759
[12] 肖寒琼, 张馨遇, 肖宇晗, 等. 基于方面词的用户消费心理画像方法[J]. 数据分析与知识发现, 2022, 6(6): 22-31
XIAO Hanqiong, ZHANG Xinyu, XIAO Yuhan, et al. Creating consumer psychology portrait with aspect words[J]. Data analysis and knowledge discovery, 2022, 6(6): 22-31
[13] 张文旭, 肖人彬, 林文广. 基于产品性能词典的评论数据驱动客户需求模型研究[J]. 中国机械工程, 2020, 31(15): 1866-1876
ZHANG Wenxu, XIAO Renbin, LIN Wenguang. Review data driven customer need model research based on product performance lexicon[J]. China mechanical engineering, 2020, 31(15): 1866-1876
[14] 刘晓敏, 李娇蓉, 陈亮, 等. 融合可拓学与多层次知识建模的仿生原型获取[J]. 机械工程学报, 2019, 55(21): 150-160
LIU Xiaomin, LI Jiaorong, CHEN Liang, et al. Bionic prototype acquisition incorporating extension and multi-level knowledge modeling[J]. Journal of mechanical engineering, 2019, 55(21): 150-160
[15] BLEI D, NG A, JORDAN M. Latent dirichlet allocation[J]. Journal of machine learning research, 2003(3): 933-1022.
[16] 杨凡. 基于LDA主题模型的在线评论聚类分析与推荐[D]. 大连: 大连理工大学, 2018.
YANG Fan. Online reviews clustering analysis and recommendation based on LDA topic model[D]. Dalian: Dalian University of Technology, 2018.
[17] SIEVERT C, SHIRLEY K. LDAvis: a method for visualizing and interpreting topics[C]//Proceedings of the Workshop on Interactive Language Learning, Visualization, and Interfaces. Stroudsburg: Association for Computational Linguistics, 2014: 63?70.
[18] 陈晓菁, 成思源, 杨雪荣. 面向专利产品创新设计的可拓变换方法研究[J]. 包装工程, 2020, 41(24): 137-142
CHEN Xiaojing, CHENG Siyuan, YANG Xuerong. Extension transform method for patent product innovation design[J]. Packaging engineering, 2020, 41(24): 137-142
[19] GRIFFIN A, HAUSER J R. The voice of the customer[J]. Marketing science, 1993, 12(1): 1-27.
[20] 高新勤, 金雨昊, 王雪萍, 等. 基于在线评论挖掘的产品感性评价方法研究[J]. 现代制造工程, 2021(12): 13-20
GAO Xinqin, JIN Yuhao, WANG Xueping, et al. Research on product perceptual evaluation method based on online review mining[J]. Modern manufacturing engineering, 2021(12): 13-20
[21] 杨春燕. 可拓创新方法[M]. 北京: 科学出版社, 2017.
[22] TURNEY P D, LITTMAN M L. Measuring praise and criticism[J]. ACM transactions on information systems, 2003, 21(4): 315-346.
[23] 彭德中, 章毅, 吕建成, 等. 一种基于SO-PMI商品评价信息的情感分析方法: CN105022805B[P]. 2018-05-04.
PENG Dezhong, ZHANG Yi, LYU Jiancheng, et al. Emotional analysis method based on SO-PMI (semantic orientation-pointwise mutual information) commodity evaluation information: CN105022805B[P]. 2018-05-04.
[24] 李文军, 杨春燕, 汤龙, 等. 可拓学中相关关系的变换方法研究[J]. 智能系统学报, 2019, 14(4): 619-626
LI Wenjun, YANG Chunyan, TANG Long, et al. Research on the transformation method for the correlation relation in extenics[J]. CAAI transactions on intelligent systems, 2019, 14(4): 619-626
[25] 花黄伟, 杨春燕. 基于因果分析的事元蕴含系及其应用[J]. 智能系统学报, 2017, 12(1): 60-66
HUA Huangwei, YANG Chunyan. A ffair-elements implication system andits application based on causal analysis[J]. CAAI transactions on intelligent systems, 2017, 12(1): 60-66
- Similar References:
Memo
-
Last Update:
1900-01-01