IEEE Style Citation: Shailaja Jadhav, Sanika Bhide, Sakshi Borse, Parimal Ghodke, Utkarsha Sane, “Validation of Warranty Defect Codes To Ensure Vehicle Quality Within Warranty,” International Journal of Computer Sciences and Engineering, Vol.7, Issue.5, pp.873-876, 2019.
MLA Style Citation: Shailaja Jadhav, Sanika Bhide, Sakshi Borse, Parimal Ghodke, Utkarsha Sane "Validation of Warranty Defect Codes To Ensure Vehicle Quality Within Warranty." International Journal of Computer Sciences and Engineering 7.5 (2019): 873-876.
APA Style Citation: Shailaja Jadhav, Sanika Bhide, Sakshi Borse, Parimal Ghodke, Utkarsha Sane, (2019). Validation of Warranty Defect Codes To Ensure Vehicle Quality Within Warranty. International Journal of Computer Sciences and Engineering, 7(5), 873-876.
BibTex Style Citation:
@article{Jadhav_2019,
author = {Shailaja Jadhav, Sanika Bhide, Sakshi Borse, Parimal Ghodke, Utkarsha Sane},
title = {Validation of Warranty Defect Codes To Ensure Vehicle Quality Within Warranty},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {5 2019},
volume = {7},
Issue = {5},
month = {5},
year = {2019},
issn = {2347-2693},
pages = {873-876},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=4329},
doi = {https://doi.org/10.26438/ijcse/v7i5.873876}
publisher = {IJCSE, Indore, INDIA},
}
RIS Style Citation:
TY - JOUR
DO = {https://doi.org/10.26438/ijcse/v7i5.873876}
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=4329
TI - Validation of Warranty Defect Codes To Ensure Vehicle Quality Within Warranty
T2 - International Journal of Computer Sciences and Engineering
AU - Shailaja Jadhav, Sanika Bhide, Sakshi Borse, Parimal Ghodke, Utkarsha Sane
PY - 2019
DA - 2019/05/31
PB - IJCSE, Indore, INDIA
SP - 873-876
IS - 5
VL - 7
SN - 2347-2693
ER -
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Abstract
Vehicle maintenance is getting increasingly important as the transport solutions become more complex and the transport industry seeks new ways of being competitive. Generally, Service Engineer receives customers claim for repair or replacement or compensation for nonperformance in the warranty period. When the customer claims his warranty, the claim contains customer voice, dealership investigation and claim manager’s action pertaining to particular “Defect Code”. Analyzing the correct defect code based on the description provided by customer requires a lot of efforts. So, our goal is to design an automated system using Natural Language Processing and Machine Learning which will decode the description and will find the most appropriate Defect Code. For this, techniques used are TF-IDF (Term Frequency-Inverse Document Frequency) and Naive Bayes Algorithm. Also, the system will help us in providing quick results, avoid wastage on time on manually validating the warranty claim by the customer. Thus, we can increase the efficiency in the process of vehicle maintenance. Completion of this project will make sure that incorrect faults are not addressed during warranty claim analysis.
Key-Words / Index Term
Defect Codes, TF-IDF, Natural Language Processing
References
[1] Alan S. Abrahim, Jian Jiao, G. Alan Wang, Weiguo Fan., “Vehicle Defect Discovery from Social Media.” Decision Support System 54 (2012) 87-97.
[2] Alan S. Abrahams, Weiguo Fan .“An Integrated Text Analytic Framework for Product Defect Discovery”, Vol. 0, No. 0, xxxx–xxxx 2014, pp. 1–16 DOI 10.1111/poms.12303 ISSN 1059-1478|EISSN 1937-5956|14|00|0001
[3] Eriks Sneiders, “Automated FAQ Answering with Question-Specific Knowledge Representation for Web Self-Service”, Catania, Italy, May 21-23, 2009
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