Sequential pattern mining algorithm for automotive warranty data

Computers and Industrial Engineering

Volumn 57, Issue 1, 2009, Pages 137-147

  Buddhakulsomsiri, Jirachai ^a   Zakarian, Armen ^b  

^a THAMMASAT UNIVERSITY   (Thailand)

^b Department of Electrical and Computer Engineering   (United States)

Author keywords

Association rule; Data mining; Sequential patterns; Warranty

Indexed keywords

DATA MINING APPLICATIONS; HIDDEN KNOWLEDGE; MANIPULATION TECHNIQUES; PRODUCT FAILURES; QUALITY ENGINEERS; RULE STRENGTH; SEQUENTIAL PATTERN MINING ALGORITHM; SEQUENTIAL PATTERNS; SEQUENTIAL RULE; SIGNIFICANT PATTERNS; WARRANTY;

ALGORITHMS; ASSOCIATION RULES; ASSOCIATIVE PROCESSING; AUTOMOTIVE INDUSTRY; DATA MINING; KNOWLEDGE MANAGEMENT; MINING;

SEQUENTIAL SWITCHING;

EID: 67349103703     PISSN: 03608352     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.cie.2008.11.006     Document Type: Article

References (56)

1. Agrawal R., and Shafer J.C. Parallel mining of association rules. IEEE Transactions on Knowledge and Data Engineering 8 6 (1996) 962-969
2. Agrawal, R., & Srikant, R. (1994). Fast algorithms for mining association rules. In Proceedings of the 20th international conference on very large databases (pp. 487-499). Santiago, Chile.
3. Agrawal, R., & Srikant, R. (1995). Mining sequential patterns. In P.S. Yu & A.L.P. Chen, Proceedings of the international conference on data engineering (pp. 3-14). Taipei, Taiwan: IEEE Computer Society.
4. Baird P. Robert Bosch Corporation failure modes effects analysis (FMEA) (2000), Read Associates, Farmington Hills, MI
5. Bayardo, R. J., & Agrawal, R. (1999). Mining the most interesting rules. In Proceedings of the 5th ACM SIGKDD international conference on knowledge discovery and data mining (pp. 145-154). San Diego, California.
6. Blischke W.R., and Murthy D.N.P. Warranty cost analysis (1994), Marcel Dekker, New York
7. Blischke W.R., and Murthy D.N.P. Product warranty handbook (1996), Marcel Dekker, New York
8. Buddhakulsomsiri J., Siradeghyan Y., Zakarian A., and Li X. Association rule generation algorithm for mining automotive warranty data. The special issue on data mining applications in engineering design, manufacturing, and logistics engineering. International Journal of Production Research 44 14 (2006) 2749-2770
9. Cali J. TQM for purchasing management (1993), McGraw Hill, New York
10. Chen E., Cao H., Li Q., and Qian T. Efficient strategies for tough aggregate constraint-based sequential pattern mining. Information Sciences 178 6 (2008) 1498-1518
11. Chen Y.L., and Hu Y.H. Constraint-based sequential pattern mining: The consideration of recency and compactness. Decision Support Systems 42 2 (2006) 1203-1215
12. Chen Y.L., and Huang T.C.K. A novel knowledge discovering model for mining fuzzy multi-level sequential patterns in sequence databases. Data and Knowledge Engineering 66 3 (2008) 349-367
13. Dhar V., and Tuzhilin A. Abstract-driven pattern discovery in databases. IEEE Transactions on Knowledge and Data Engineering 5 6 (1993) 926-938
14. Feng J., Wang J., and Wang J. An optimization model for concurrent selection of tolerances and suppliers. Computers and Industrial Engineering 40 (2001) 15-33
15. Fiot C., Laurent A., and Teisseire M. From crispness to fuzziness: Three algorithms for soft sequential pattern mining. IEEE Transactions on Fuzzy Systems 15 6 (2007) 1263-1277
16. Fredette M., and Lawless J.F. Finite-horizon prediction of recurrent events, with application to forecasts of warranty claims. Technometrics 49 1 (2007) 66-80
17. Garcia-Molina H., Ullman J.D., and Widom J.D. Database systems: The complete book (2001), Prentice Hall, New Jersey
18. Gutiérrez-Pulido H., Aguirre-Torres V., and Christen J.A. A Bayesian approach for the determination of warranty length. Journal of Quality Technology 38 2 (2006) 180-189
19. Han J., and Kamber M. Data mining: Concept and techniques (2006), Morgan Kaufman, San Francisco, CA
20. Hotz, E., Grimmer, U., Heuser, W., Nakhaeizadeh, G., & Wieczorek, M. (2001). REVI-MINER, A KDD-environment for deviation detection and analysis of warranty and goodwill cost statements in automotive industry. In Proceedings of the 7th ACM SIGKDD international conference on knowledge discovery and data mining (pp. 431-437). San Francisco, CA.
21. Hotz, E., Nakhaeizadeh, G., Petzsche, B., & Spiegelberger, H. (1999). WAPS, A data mining support environment for the planning of warranty and goodwill costs in the automobile industry. In Proceedings of the 5th ACM SIGKDD international conference on knowledge discovery and data mining (pp. 417-419). San Diego, CA.
22. Hu X.J., and Lawless J.F. Estimation from truncated lifetime data with supplementary information on covariates and censoring times. Biometrika 83 (1996) 747-761
23. Jung M., and Bai D.S. Analysis of field data under two-dimensional warranty. Reliability Engineering and System Safety 92 2 (2007) 135-143
24. Kalbfleisch J.D., Lawless J.F., and Robinson J.A. Methods for the analysis and prediction of warranty claims. Technometrics 33 (1991) 228-273
25. Karim M.R., Yamamoto W., and Suzuki K. Statistical analysis of marginal count failure data. Lifetime Data Analysis 7 (2001) 173-186
26. Kulkarni V., and Resnick S.I. Warranty claims modeling. Naval Research Logistics 55 4 (2008) 339-349
27. Kum H.C., Chang J.H., and Wang W. Sequential pattern mining in multi-databases via multiple alignment. Data Mining and Knowledge Discovery 12 2-3 (2006) 151-180
28. Kum H.C., Chang J.H., and Wang W. Benchmarking the effectiveness of sequential pattern mining methods. Data and Knowledge Engineering 60 1 (2007) 30-50
29. Kuo R.J., Chao C.M., and Liu C.Y. Integration of K-means algorithm and AprioriSome algorithm for fuzzy sequential pattern mining. Applied Soft Computing Journal 9 1 (2009) 85-93
30. Laur P.A., Symphor J.E., Nock R., and Poncelet P. Statistical supports for mining sequential patterns and improving the incremental update process on data streams. Intelligent Data Analysis 11 1 (2007) 29-47
31. Lawless J.F. Statistical analysis of product warranty data. International Statistical Review 66 (1998) 41-60
32. Lawless J.F., and Kalbfleisch J.D. Some issues in the collection and analysis of field reliability data. In: Klein J.P., and Goel P.K. (Eds). Survival analysis: State of the art (1992), Kluwer, Amsterdam 141-152
33. Li, W., Han, J., & Pei, J. (2001) CMAR: Accurate and efficient classification based on multiple class association rules. In ICDM 2001, IEEE Computer Society (pp. 369-376). San Jose, CA.
34. Lin N.P., Chen H.J., Hao W.H., Chueh H.E., and Chang C.I. Mining strong positive and negative sequential patterns. WSEAS Transactions on Computers 7 3 (2008) 119-124
35. Lu M.W. Automotive reliability prediction based on early field failure warranty data. Quality and Reliability Engineering International 14 (1998) 103-108
36. Majeske K.D. A non-homogeneous Poisson process predictive model for automobile warranty claims. Reliability Engineering and System Safety 92 2 (2007) 243-251
37. Majeske, K. D., & Herrin, G. D. (1995). Assessing mixture model goodness-of-fit with an application to automobile warranty data. In Proceedings of the annual reliability and maintainability symposium (pp. 378-383). Washington, DC.
38. Majeske K.D., Lynch T.C., and Herrin G.D. Evaluating product and process design changes with warranty data. International Journal of Production Economics 50 (1997) 79-89
39. Masseglia F., Poncelet P., and Teisseire M. Efficient mining of sequential patterns with time constraints: Reducing the combinations. Expert Systems with Applications 36 2 (2008) 2677-2690
40. Murthy D.N.P., and Djamaludin I. New product warranty: A literature review. International Journal of Production Economics 79 (2002) 231-260
41. Murthy D.N.P., Djamaludin I., and Wilson R.J. A consumer incentive warranty policy and servicing strategy for products with uncertain quality. Quality and Reliability Engineering International 11 (1995) 155-163
42. Pawlak Z. Rough set approach to knowledge-based decision support. European Journal of Operational Research 99 (1997) 48-57
43. Pei J., Han J., Mortazavi-Asl B., Wang J., Pinto H., Chen Q., et al. Mining sequential patterns by pattern-growth: The PrefixSpan approach. IEEE Transactions on Knowledge and Data Engineering 16 11 (2004) 1424-1440
44. Piatetsky-Shapiro, G. (1991). Discovery, analysis, and presentation of strong rules. In: G. Piatetsky-Shapiro and W.J. Frawley, Knowledge discovery in databases (pp. 229-248). AAAI/MIT Press.
45. Polatoglu H., and Sahin I. Probability distributions of cost, revenue and profit over a warranty cycle. European Journal of Operational Research 108 (1998) 170-183
46. Ren J., Sun Y., and Guo S. Incremental sequential pattern mining based on constraints. Journal of Computational Information Systems 4 2 (2008) 571-576
47. Robinson J.A., and McDonald G.C. Issues related to field reliability data. In: Liepins G.E., and Uppuluri V.R.R. (Eds). Data quality control: Theory and pragmatics (1991), Marcel Dekker, New York 69-90
48. Sahin I., and Polatoglu H. Quality warranty and preventive maintenance (1998), Kluwer, Boston
49. Siradeghyan Y., Zakarian A., and Mohanty P. Entropy based associative classification algorithm for mining manufacturing data. International Journal of Computer Integrated Manufacturing 20 (2008) 25
50. Singpurwalla N.D., and Wilson S.P. Failure models indexed by two scales. Advances in Applied Probability 30 (1998) 1058-1072
51. Suzuki K., Yamamoto W., Karim M.R., and Wang L. Data analysis based on warranty database. In: Limnios N., and Nikulin M. (Eds). Recent advances in reliability theory: Methodology, practice, and inference (2000), Birkhauser, Boston 213-227
52. Suzuki K., Karim M.R., and Wang L. Statistical analysis of reliability warranty data. In: Balakrishnan N., and Rao C.R. (Eds). Handbook of statistics 20 advances in reliability (2001), Elsevier, London 585-609
53. Thomas, S., & Sarawagi, S. (1998). Mining generalized association rules and sequential patterns using SQL queries. In Proceeding of the 4th international conference on knowledge discovery in databases and data mining (pp. 3-17). New York.
54. Wang L., and Suzuki K. Nonparametric estimation of lifetime distribution from warranty data without monthly unit sales information. Journal of the Reliability Engineering Association of Japan 23 (2001) 145-154
55. Yin, X., & Han, J. (2003). CPAR: Classification based on Predictive Association Rules, In Proc. 2003 SIAM int. conf. data mining (SDM'03).
56. Yun U. A new framework for detecting weighted sequential patterns in large sequence databases. Knowledge-Based Systems 21 2 (2008) 110-122