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Integrating data mining and rough set for customer group-based discovery of product configuration rules

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References

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2016Data-driven innovation to capture user-experience product design: An empirical study for notebook visual aesthetics design80 cited
2013Product service system configuration based on support vector machine considering customer perception63 cited
2008Prediction of manufacturing resource requirements from customer demands in mass-customisation production

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2012A constraint satisfaction approach to resolving product configuration conflicts38 cited

2007A framework for generating product production information for mass customization35 cited

2013Product customization of tablet computers based on the information of online reviews by customers34 cited

2009Customer-driven product design and evaluation method for collaborative design environments33 cited

2009Personalized product configuration rules with dual formulations: A method to proactively leverage mass confusion33 cited

2011Applying constraint satisfaction approach to solve product configuration problems with cardinality-based configuration rules30 cited

2008Integrating rough set clustering and grey model to analyse dynamic customer requirements30 cited

2008Multi-objective product configuration involving new components under uncertainty30 cited

2015An approach to rule extraction for product service system configuration that considers customer perception30 cited

2011An association rule mining and maintaining approach in dynamic database for aiding product–service system conceptual design29 cited

2010Aided analysis for quality function deployment with an Apriori-based data mining approach26 cited