Research and Application of Product Design User Requirements Mining Based on Online Comments and Kano Model

Zhiyuan Wang

Abstract


To solve the problems of solid subjectivity, fewer data, and poor real-time performance of user demand mining in product design, this paper proposes a method of user demand mining based on online reviews and the Kano model. Firstly, Octopus crawls the user's online comment data, and the text data is preprocessed by jieba to form a comment dataset. Then the data is classified and labeled by word segmentation. Secondly, the Apriori algorithm is used to extract the product attributes that users pay attention to frequently, and the SO-PMI is used to calculate the product attribute evaluation value. Finally, with the help of the KANO model, the user demand classification of product attributes is carried out, the priority ranking of product attributes is obtained, and then the direction of product optimization and improvement is proposed. A fire rescue drone product is taken as an example to verify the effectiveness of the proposed method. The results show that this method can provide valuable information about user requirements, improve user satisfaction, and promote the successful development of product design.


Full Text:

PDF

References


Cory R.Schaffhausen,Timothy M. Kowalewski.Assessing the quality of unmet user requirements: Effects of need statement characteristics: design Studies,2016, 44:1-27.

SALEHAN M, KIMDJ.Predicting the performance of online consumer reviews: A

sentiment mining approach to big data analytics.Decision Support Systems,2016,81:30-40.

JIN J,LIU Y, JI P, et al. Review recent advances in information mining from big consumer opinion data for product design. Journal of Computing and Information Science In Engineering,2019,19(1):010801.

ZHANG L, WU L, MATTILA A S.Online reviews.Journal of Travel Research.2015,7(4):e3-e5.

JIN J, JI P, GU R. Identifying comparative customer requirements from online product reviews for competitor analysis.Engineering Applications of Artificial Intelligence.2016.49:6l-73.

QI J Y,ZHANG Z,JEON S,et al.Mining customer require ments from online reviews:a product improvement perspective.Information&Management.2016,53(8):951 963.

WANG Keqin, LIU Zhaoming. Product design improvement based on importance performance

competitor analysis of online reviews. Computer Integrated Manufacturing Systems,2022,28(05):1496-1506.

YANG Cheng,TAN Kun, YU Chunyang.Mobil phone product improvement based on big data of comment.Computer Integrated Manufacturing Systems,2020,26(11):3074-3083.

WANG Ying,ZHENG Liwei,ZHANG Shuyao,ZHANG Xiaoyun.Software Requirement

Mining Method for Chinese APP Uer Review Data.Computer Science,2020,47(12):56-6.

JIA Danpin,JIN Jian,GENG QIAN,DENG Siyu.A Kansei Engineering Integrated

Approach for Customer-needs Mining from Online Product Reviews. Journal of the China Society for Scientific and Technical Information,2020,39(03):308-316.

YANG Huan.The integration of data and design-research on the innovation path of extensive data analysis to derive user demand insights.Decoration,2019(5):100-103.

LI Shaobo,QUAN Huafeng,Hu Jianjun,WU Yongming,ZHANG Ansi.Perceptual evaluation method of products based on online reviews data-driven.Computer Integrated Manufacturing Systems,2018,24(03):752-762.

LI Xiang,HU Yun,WANG YiLI.Research on Product User Demand Insight Method Based on SPSS and Online Comment Analysis.Packaging Engineering,2022,43(02):106-115.

JI Xue,GAO QI,LI Xianfei,GAO Fei.Reviews mining and requirements elicitation methodology considering product attributes’ hierarchy.Computer Integrated Manufacturing

Systems,2020,26(03):747-759.

WANG Jun, LIU Siyi.Research on Product Design Method by Online Review Text Driven.Machine Design and Research,2022,38(04):1-5+11.

Chatterjee P.Online Reviews: Do Consumers Use Them.Advances in Consumer Research,2001,28.

WANG Xue, DONG Qingxing,ZHANG Bin.Analytical Framework and Empirical Study of User Needs for Online Reviews Based on KANO Model. Information studies: Theory & Application,2022,45(02):160-167.

KANO N,SERAKU N, TAKAHASHI F.Attractive quality and must-be quality[J]. The Journal of the Japanese Society for Quality Control,1984,14( 2): 39-48.

KIM H,KIM D,YANG H,et al.Development of a wall-climbing robot using a tracked wheel mechanism[J]. Journal of Mechanical Science&Technology,2008,22( 8) : 1490-1498.

LUO Le, GEQidong, ZHOU Yongxue, XIA Bin. Association Rule Mining of Equipment Data Based on Apriori Algorithm. Command Control & Simulation,2021,43(06):29-33.

LI Jiangyong,Zhang Wei.Product Improvement Design from the Perspective of Online Comment Data Mining.Packaging Engineering,2021,42(06):135-141.

WANG Ke, XAI Rui.A Survey on Automatical Construction Methods of Sentiment

Lexicons.Acta Automatica Sinica,2016,42(04):495-511.

Jakob N, Gurevych I.Extracting Opinion Targets in a Single- and Cross-Domain Setting with Conditional Random Fields[C]//Conference on Empirical Methods in Natural Language Processing.2010.

ZHAOYanyan, QIN Bin, CHE Wanxiang, LIU Ting.Appraisal Expression Recognition Based on Syntactic Path.Journal of Software,2011,22(05):887-898.

WANG Keqin,PEI Fengjun.Online Comment Mining for Product Design.Improvement

[J]. Computer Engineering and Applications,2019,55(19):235-245.

Loiseau P,Gon calves P,Dewaele G,et al.Investigating self-similarity and heavy-tailed

distributions on a large-scale experimental facility.IEEE/ACM Transactions on Networking,2010,18(4)1261-1274.

Stegeman A. Heavy tails versus long-range dependence in self-similar network traffic[J].Statistica Neerlandica,2010,54(3):293-314.

YAO Tianfang,LOU Decheng.Research on Semantic Orientation Analysis for Topics in Chinese Sentences.Journal of Chinese Information Processing,2007(05):73-79.

Song, H., Chen, C. and Yu, Q., 2018, March. Research on the Kano model based on online comment data mining. In 2018 IEEE 3rd International Conference on Big Data Analysis (ICBDA) (pp. 76-82). IEEE.

Min, H., Yun, J. and Geum, Y., 2018. Analyzing dynamic change in customer requirements: An approach using review-based Kano analysis. Sustainability, 10(3), p.746.

Ginting, R., Hidayati, J. and Siregar, I., 2018, March. Integrating Kano’s model into quality function deployment for product design: A comprehensive review. In IOP Conference Series: Materials Science and Engineering (Vol. 319, No. 1, p. 012043). IOP Publishing.

Zhang, J., Chen, D. and Lu, M., 2018. Combining sentiment analysis with a fuzzy Kano model for product aspect preference recommendation. IEEE Access, 6, pp.59163-59172.

Ireland, R. and Liu, A., 2018. Application of data analytics for product design: Sentiment analysis of online product reviews. CIRP Journal of Manufacturing Science and Technology, 23, pp.128-144.

Li, S. and Li, Y., 2018, May. Sentiment analysis of online reviews based on the word alignment model: a product improvement perspective. In 2018 2nd IEEE Advanced Information Management, Communicates, Electronic and Automation Control Conference (IMCEC) (pp. 2226-2231). IEEE.

Jin, J., Jia, D. and Chen, K., 2022. Mining online reviews with a Kansei-integrated Kano model for innovative product design. International Journal of Production Research, 60(22), pp.6708-6727.

Li, M. and Zhang, J., 2021. Integrating Kano model, AHP, and QFD methods for new product development based on text mining, intuitionistic fuzzy sets, and customers satisfaction. Mathematical Problems in Engineering, 2021, pp.1-17.




DOI: https://doi.org/10.31449/inf.v47i10.4909

Creative Commons License
This work is licensed under a Creative Commons Attribution 3.0 License.