In recent years, the automobile industry has been making efforts to develop vehicles that satisfy customers' emotions rather than malfunctions. The Vehicle Dependability Study(VDS) has been strengthened emotion items since the introduction of the new evaluation system VDS3 from 2015. The ratio of emotion items increased from 11% to 25%. In order to clarify the problem and cause of emotion items, we analyzed verbatim which is the customers' complaint data provided by J.D power every year, but it was difficult to extract customers' intention because the number of verbatim is small and expressed in terms of customer’s term rather than engineer’s term. To solve the problem, we are additionally colleting big data such as internet, warranty, online survey. Since the amount of data is very large, we developed textmining techniques such as dictionary, topic, Support Vector Machine(SVM), n-gram to improve process. And we developed the Internet Data Search(IDS) program that everyone in the company can use by web.


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    Title :

    Customer Complaints Analysis Using Textmining Method


    Additional title:

    Sae Technical Papers


    Contributors:
    You, Hanmin (author)

    Conference:

    WCX SAE World Congress Experience ; 2022



    Publication date :

    2022-03-29




    Type of media :

    Conference paper


    Type of material :

    Print


    Language :

    English