Technical Paper
Development of Automatic Classification of Customer Complaints Using Deep Learning
2024-04-09
2024-01-2789
In recent years, the automotive industry has been making efforts to develop vehicles that satisfy customers' emotions rather than malfunctions by improving the durability of vehicles. The VDS(Vehicle Dependability Study) is index which is the number of complaints per 100 units released by J.D. POWER in every year. It investigates customers who have used it for 3 years after purchasing a new car and consists of 177 specific problems grouped into 8 major vehicle categories such as PT, ACEN, FCD, Exterior. The VDS has been strengthened since the introduction of the new evaluation system VDS3 in 2015. In order to improve the VDS index, it is important to gather various customer complaints such as internet data, claim data, enprecis data and clarify the problem and cause. enprecis data is survey of customer complaints by on-line in terms of VDS.