A multi-objective PSO approach of mining association rules for affective design based on online customer reviews

References

• Agrawal, R., and R. Srikant. 1994. “Fast Algorithms for Mining Association Rules in Large Databases.” In Proceedings of the 20th International Conference on Very Large Data Bases, 487–499, Santiago, September 12–15.
   Google Scholar
• Baccianella, S., A. Esuli, and F. Sebastiani. 2010. “SentiWordNet 3.0: An Enhanced Lexical Resource for Sentiment Analysis and Opinion Mining.” In Proceedings of the 7th Conference on Language Resources and Evaluation (LREC’10), 2200–2204, Valletta, May 17–23.
   Google Scholar
• Barnes, C., and S. P. Lillford. 2009. “Decision Support for the Design of Affective Products.” Journal of Engineering Design 20 (5): 477–492. doi: 10.1080/09544820902875041
   Web of Science ®Google Scholar
• Barone, S., A. Lombardo, and P. Tarantino. 2007. “A Weighted Logistic Regression for Conjoint Analysis and Kansei Engineering.” Quality and Reliability Engineering International 23 (6): 689–706. doi: 10.1002/qre.866
   Web of Science ®Google Scholar
• Beiranvand, V., M. Mobasher-Kashani, and A. A. Bakar. 2014. “Multi-Objective PSO Algorithm for Mining Numerical Association Rules Without a Priori Discretization.” Expert Systems with Applications 41: 4259–4273. doi: 10.1016/j.eswa.2013.12.043
   Web of Science ®Google Scholar
• Chan, K. Y., C. K. Kwong, T. S. Dillon, and K. Y. Fung. 2011. “An Intelligent Fuzzy Regression Approach for Affective Product Design That Captures Nonlinearity and Fuzziness.” Journal of Engineering Design 22 (8): 523–542. doi: 10.1080/09544820903550924
   Web of Science ®Google Scholar
• Chang, H. C., H. H. Lai, and Y. M. Chang. 2007. “A Measurement Scale for Evaluating the Attractiveness of a Passenger Car Form Aimed at Young Consumers.” International Journal of Industrial Ergonomics 37 (1): 21–30. doi: 10.1016/j.ergon.2006.09.014
   Web of Science ®Google Scholar
• Chen, X., C. H. Chen, K. F. Leong, and X. Jiang. 2013. “An Ontology Learning System for Customer Needs Representation in Product Development.” The International Journal of Advanced Manufacturing Technology 67 (1-4): 441–453. doi: 10.1007/s00170-012-4496-2
   Web of Science ®Google Scholar
• Chung, W., and T. L. Tseng. 2012. “Discovering Business Intelligence from Online Product Reviews: A Rule-Induction Framework.” Expert Systems with Applications 1 (1): 1–10.
   Google Scholar
• Decker, R., and M. Trusov. 2010. “Estimating Aggregate Consumer Preferences from Online Product Reviews.” International Journal of Research in Marketing 27 (4): 293–307. doi: 10.1016/j.ijresmar.2010.09.001
   Web of Science ®Google Scholar
• Dehuri, S., A. Jagadev, A. Ghosh, and R. Mall. 2006. “Multi-Objective Genetic Algorithm for Association Rule Mining Using a Homogeneous Dedicated Cluster of Workstations.” American Journal of Applied Sciences 3 (11): 2086–2095. doi: 10.3844/ajassp.2006.2086.2095
   Google Scholar
• Dehuri, S., S. Patnaik, A. Ghosh, and R. Mall. 2008. “Application of Elitist Multiobjective Genetic Algorithm for Classification Rule Generation.” Applied Soft Computing 8 (1): 477–487. doi: 10.1016/j.asoc.2007.02.009
   Web of Science ®Google Scholar
• Fung, K. Y., C. K. Kwong, K. W. M. Siu, and K. M. Yu. 2012. “A Multi-Objective Genetic Algorithm Approach to Rule Mining for Affective Product Design.” Expert Systems with Applications 39 (8): 7411–7419. doi: 10.1016/j.eswa.2012.01.065
   Web of Science ®Google Scholar
• Ghosh, A., and B. Nath. 2004. “Multi-Objective Rule Mining Using Genetic Algorithms.” Information Sciences 163 (1-3): 123–133. doi: 10.1016/j.ins.2003.03.021
   Web of Science ®Google Scholar
• Han, S. H., M. H. Yun, K. J. Kim, and J. Kwak. 2000. “Evaluation of Product Usability: Development and Validation of Usability Dimensions and Design Elements Based on Empirical Models.” International Journal of Industrial Ergonomics 26 (4): 477–488. doi: 10.1016/S0169-8141(00)00019-6
   Web of Science ®Google Scholar
• Houtsma, M., and A. Swami. 1995. “Set-Oriented Mining for Association Rules in Relational Databases.” In Proceedings of the Eleventh International Conference on Data Engineering, 25–33, Taipei, March 6–10.
   Google Scholar
• Hsiao, S. W., and H. C. Tsai. 2005. “Applying a Hybrid Approach Based on Fuzzy Neural Network and Genetic Algorithm to Product Form Design.” International Journal of Industrial Ergonomics 35 (5): 411–428. doi: 10.1016/j.ergon.2004.10.007
   Web of Science ®Google Scholar
• Jiang, H., C. K. Kwong, K. W. M. Siu, and Y. Liu. 2015. “Rough Set and PSO-Based ANFIS Approaches to Modeling Customer Satisfaction for Affective Product Design.” Advanced Engineering Informatics 29 (3): 727–738. doi: 10.1016/j.aei.2015.07.005
   Web of Science ®Google Scholar
• Jiao, R. J., Y. Zhang, and M. Helander. 2006. “A Kansei Mining System for Affective Design.” Expert Systems with Applications 30 (4): 658–673. doi: 10.1016/j.eswa.2005.07.020
   Web of Science ®Google Scholar
• Jin, J., P. Ji, and Y. Liu. 2012. “Product Characteristic Weighting for Designer from Online Reviews: An Ordinal Classification Approach.” In EDBT-ICDT ‘12 Proceedings of the 2012 Joint EDBT/ICDT Workshops, 33–40, Berlin, March 30–30.
   Google Scholar
• Jin, J., Y. Liu, P. Ji, and H. Liu. 2016. “Understanding Big Consumer Opinion Data for Market-Driven Product Design.” International Journal of Production Research 54 (10): 3019–3041. doi: 10.1080/00207543.2016.1154208
   Web of Science ®Google Scholar
• Kennedy, J., and R. Eberhart. 1995. “Particle Swarm Optimization.” In Proceedings of the 1995 IEEE International Conference on Neural Networks Vol. 4, 1942–1948, Perth, November 27–December 1.
   Google Scholar
• Lai, H. H., Y. M. Chang, and H. C. Chang. 2005a. “A Robust Design Approach for Enhancing the Feeling Quality of a Product: A Car Profile Case Study.” International Journal of Industrial Ergonomics 35 (5): 445–460. doi: 10.1016/j.ergon.2004.10.008
   Web of Science ®Google Scholar
• Lai, H. H., Y. C. Lin, and C. H. Yeh. 2005b. “Form Design of Product Image Using Grey Relational Analysis and Neural Network Models.” Computers & Operations Research 32 (10): 2689–2711. doi: 10.1016/j.cor.2004.03.021
   Web of Science ®Google Scholar
• Lau, T. W., P. C. L. Hui, F. S. F. Ng, and K. C. C. Chan. 2006. “A New Fuzzy Approach to Improve Fashion Product Development.” Computers in Industry 57 (1): 82–92. doi: 10.1016/j.compind.2005.04.003
   Web of Science ®Google Scholar
• Lee, T. 2009. “Automatically Learning User Needs from Online Reviews for New Product Design.” In America Conference on Information Systems, 1–9, San Francisco, CA, August 6–9.
   Google Scholar
• Lim, S., and C. S. Tucker. 2016. “A Bayesian Sampling Method for Product Feature Extraction from Large-Scale Textual Data.” Journal of Mechanical Design 138 (6): 061403. doi: 10.1115/1.4033238
   Web of Science ®Google Scholar
• Lin, D. I., and Z. M. Kedem. 2002. “Pincer-Search: An Efficient Algorithm for Discovering the Maximal Frequent Set.” IEEE Transactions on Knowledge and Data Engineering 14 (3): 553–566. doi: 10.1109/TKDE.2002.1000342
   Web of Science ®Google Scholar
• Lin, Y. C., H. H. Lai, and C. H. Yeh. 2007. “Consumer-Oriented Product Form Design Based on Fuzzy Logic: A Case Study of Mobile Phones.” International Journal of Industrial Ergonomics 37 (6): 531–543. doi: 10.1016/j.ergon.2007.03.003
   Web of Science ®Google Scholar
• Lu, X. 2014. Computational Methods for Corpus Annotation and Analysis. Dordrecht: Springer.
   Google Scholar
• Minaei-Bidgoli, B., R. Barmaki, and M. Nasiri. 2013. “Mining Numerical Association Rules via Multi-Objective Genetic Algorithms.” Information Sciences 233 (1): 15–24. doi: 10.1016/j.ins.2013.01.028
   Google Scholar
• Nagamachi, M. 1995. “Kansei Engineering: A New Ergonomic Consumer-Oriented Technology for Product Development.” International Journal of Industrial Ergonomics 15 (1): 3–11. doi: 10.1016/0169-8141(94)00052-5
   Web of Science ®Google Scholar
• Nagamachi, M. 2008. “Perspectives and the New Trend of Kansei/Affective Engineering.” The TQM Journal 20 (4): 290–298. doi: 10.1108/17542730810881285
   Google Scholar
• Nishino, T., M. Nagamachi, and H. Tanaka. 2006. “Variable Precision Bayesian Rough Set Model and its Application to Kansei Engineering.” Lecture Notes in Computer Science 4100: 190–206. doi: 10.1007/11847465_9
   Google Scholar
• Noble, C. H., and M. Kumar. 2008. “Using Product Design Strategically to Create Deeper Consumer Connections.” Business Horizons 51 (5): 441–450. doi: 10.1016/j.bushor.2008.03.006
   Web of Science ®Google Scholar
• Ozbakir, L., A. Baykasoglu, S. Kulluk, and H. Yapıcı. 2009. “TACO-Miner: An Ant Colony Based Algorithm for Rule Extraction from Trained Neural Networks.” Expert Systems with Applications 36 (10): 12295–12305. doi: 10.1016/j.eswa.2009.04.058
   Web of Science ®Google Scholar
• Park, J., and S. H. Han. 2004. “A Fuzzy Rule-Based Approach to Modeling Affective User Satisfaction Towards Office Chair Design.” International Journal of Industrial Ergonomics 34 (1): 31–47. doi: 10.1016/j.ergon.2004.01.006
   Web of Science ®Google Scholar
• Rahmath, P. H., and T. Ahmad. 2014. “Fuzzy Based Sentiment Analysis of Online Product Reviews Using Machine Learning Techniques.” International Journal of Computer Applications 99 (17): 9–16. doi: 10.5120/17463-8243
   Google Scholar
• Rai, R. 2012. “Identifying Key Product Attributes and Their Importance Levels from Online Customer Reviews.” In 38th Design Automation Conference, 533–540, Chicago, IL, August 12–15.
   Google Scholar
• Ranscombe, C., B. Hicks, G. Mullineux, and B. Singh. 2012. “Visually Decomposing Vehicle Images: Exploring the Influence of Different Aesthetic Features on Consumer Perception of Brand.” Design Studies 33 (4): 319–341. doi: 10.1016/j.destud.2011.06.006
   Web of Science ®Google Scholar
• Sarath, K. N. V. D., and V. Ravi. 2013. “Association Rule Mining Using Binary Particle Swarm Optimization.” Engineering Applications of Artificial Intelligence 26 (8): 1832–1840. doi: 10.1016/j.engappai.2013.06.003
   Web of Science ®Google Scholar
• Sekkeli, G., G. Koksal, I. Batmaz, and O. T. Bayrak. 2010. “Classification Models Based on Tanaka’s Fuzzy Linear Regression Approach: The Case of Customer Satisfaction Modeling.” Journal of Intelligent & Fuzzy Systems 21 (5): 341–351.
   Web of Science ®Google Scholar
• Seva, R. R., H. B. L. Duh, and M. G. Helander. 2007. “The Marketing Implications of Affective Product Design.” Applied Ergonomics 38 (6): 723–731. doi: 10.1016/j.apergo.2006.12.001
   PubMed Web of Science ®Google Scholar
• Shi, Y., and R. Eberhart. 1998. “A Modified Particle Swarm Optimizer.” In The 1998 IEEE International Conference on Evolutionary Computation, 69–73, Anchorage, May 4–9.
   Google Scholar
• Tsai, H. C., S. W. Hsiao, and F. K. Hung. 2006. “An Image Evaluation Approach for Parameter-Based Product form and Color Design.” Computer-Aided Design 38 (2): 157–171. doi: 10.1016/j.cad.2005.10.001
   Web of Science ®Google Scholar
• Tuarob, S., and C. Tucker. 2013. “Fad or Here to Stay: Predicting Product Market Adoption and Longevity Using Large Scale, Social Media Data.” In 33rd Computers and Information in Engineering Conference, 1–13, Portland, OR, August 4–7.
   Google Scholar
• Tuarob, S., and C. S. Tucker. 2015a. “Automated Discovery of Lead Users and Latent Product Features by Mining Large Scale Social Media Networks.” Journal of Mechanical Design 137 (7): 071402. doi: 10.1115/1.4030049
   Web of Science ®Google Scholar
• Tuarob, S., and C. S. Tucker. 2015b. “Quantifying Product Favorability and Extracting Notable Product Features Using Large Scale Social Media Data.” Journal of Computing and Information Science in Engineering 15 (3): 031003. doi: 10.1115/1.4029562
   Web of Science ®Google Scholar
• Wang, H., and W. Wang. 2014. “Product Weakness Finder: An Opinion-Aware System Through Sentiment Analysis.” Industrial Management & Data Systems 114 (8): 1301–1320. doi: 10.1108/IMDS-05-2014-0159
   Web of Science ®Google Scholar
• Xu, K., S. S. Liao, J. Li, and Y. Song. 2011. “Mining Comparative Opinions from Customer Reviews for Competitive Intelligence.” Decision Support Systems 50 (4): 743–754. doi: 10.1016/j.dss.2010.08.021
   Web of Science ®Google Scholar
• Yadav, H. C., R. Jain, A. R. Singh, and P. K. Mishra. 2017. “Kano Integrated Robust Design Approach for Aesthetical Product Design: A Case Study of a Car Profile.” Journal of Intelligent Manufacturing 28 (7): 1709–1727. doi: 10.1007/s10845-016-1202-5
   Web of Science ®Google Scholar
• Yan, X., C. Zhang, and S. Zhang. 2009. “Genetic Algorithm-Based Strategy for Identifying Association Rules Without Specifying Actual Minimum Support.” Expert Systems with Applications 36 (2): 3066–3076. doi: 10.1016/j.eswa.2008.01.028
   Web of Science ®Google Scholar
• Yang, L., B. Liu, H. Lin, and Y. Lin. 2016. “Combining Local and Global Information for Product Feature Extraction in Opinion Documents.” Information Processing Letters 116 (10): 623–627. doi: 10.1016/j.ipl.2016.04.009
   Web of Science ®Google Scholar
• You, H., T. Ryu, K. Oh, M. H. Yun, and K. J. Kim. 2006. “Development of Customer Satisfaction Models for Automotive Interior Materials.” International Journal of Industrial Ergonomics 36 (4): 323–330. doi: 10.1016/j.ergon.2005.12.007
   Web of Science ®Google Scholar
• Zhai, L. Y., L. P. Khoo, and Z. W. Zhong. 2009. “A Dominance-Based Rough Set Approach to Kansei Engineering in Product Development.” Expert Systems with Applications 36 (1): 393–402. doi: 10.1016/j.eswa.2007.09.041
   Web of Science ®Google Scholar
• Zhang, K., R. Narayanan, and A. Choudhary. 2010. “Voice of the Customers: Mining Online Customer Reviews for Product Feature-Based Ranking.” In Proceedings of the 3rd Wonference on Online Social Networks, 1–9, Boston, June 22–25.
   Google Scholar
• Zhang, H., A. Sekhari, Y. Ouzrout, and A. Bouras. 2016. “Jointly Identifying Opinion Mining Elements and Fuzzy Measurement of Opinion Intensity to Analyze Product Features.” Engineering Applications of Artificial Intelligence 47: 122–139. doi: 10.1016/j.engappai.2015.06.007
   Web of Science ®Google Scholar
• Zhou, F., R. J. Jiao, and J. S. Linsey. 2015. “Latent Customer Needs Elicitation by Use Case Analogical Reasoning from Sentiment Analysis of Online Product Reviews.” Journal of Mechanical Design 137 (7): 071401. doi: 10.1115/1.4030159
   Web of Science ®Google Scholar
• Zhou, F., R. J. Jiao, D. Schaefer, and S. Chen. 2009. “Rough Set Based Rule Mining for Affective Design.” In International Conference on Engineering Design, 245–254, Stanford, CA, AUGUST 24–27.
   Google Scholar
• Zimmermann, M., E. Ntoutsi, and M. Spiliopoulou. 2015. “Discovering and Monitoring Product Features and the Opinions on Them with OPINSTREAM.” Neurocomputing 150 (Part A): 318–330. doi: 10.1016/j.neucom.2014.04.079
   Google Scholar