Data quality awareness: A case study for cost optimal association rule mining

Knowledge and Information Systems

Volumn 11, Issue 2, 2007, Pages 191-215

  Berti Équille, Laure ^a  

^a UNIVERSITÉ DE RENNES 1   (France)

Author keywords

Association rule mining; Cost model; Data quality management; Data quality metadata; Quality awareness mining

Indexed keywords

ASSOCIATION RULES; DATA REDUCTION; QUALITY MANAGEMENT;

COST MODELING; DATA QUALITY; DATA QUALITY MANAGEMENT; INTERESTINGNESS MEASURES; KNOWLEDGE DISCOVERY AND DATA MININGS; PROBABILISTIC MODELING; QUALITY AWARENESS; SUPPORT AND CONFIDENCE;

DATA MINING;

EID: 33947395207     PISSN: 02191377     EISSN: 02193116     Source Type: Journal    
DOI: 10.1007/s10115-006-0006-x     Document Type: Article

References (68)

1. Avenali A, Batini C, Bertolazzi P, Missier P (2004) A formulation of the data quality optimization problem. In: Proceedings of the international CAiSE workhop on data and information quality (DIQ), Riga, Latvia, pp 49-63
2. Ballou DP, Pazer H (1995) Designing information systems to optimize the accuracy-timeliness trade-off. Inf Syst Res 6(1)
3. Ballou DP, Pazer H (2002) Modeling completeness versus consistency trade-offs in information decision contexts. IEEE Trans Knowl Data Eng (TDKE) 15(1):240-243
4. Batini C, Catarci T, Scannapiceco M (2004) A survey of data quality issues in cooperative information systems. In: Tutorial presented at the 23rd international conference on conceptual modeling (ER), Shanghai, China
5. Benjelloun O, Garcia-Molina H, Su Q, Widom J (2005) Swoosh: A generic approach to entity resolution. Technical Report, Stanford Database Group
6. Berti-Équille L, Moussouni F (2005) Quality-aware integration and warehousing of genomic data. In: Proceedings of the 10th international conference on information quality (IQ'05), MIT, Cambridge, USA
7. Bilenko M, Mooney RJ (2003) Adaptive duplicate detection using learnable string similarity measures. In: Proceedings of the 9th ACM SIGKDD conference on knowledge discovery and data mining (KDD), Washington, DC, USA, pp 39-48
8. Bouzeghoub M, Peralta V (2004) A framework for analysis of data freshness. In: Proceedings of the 1st ACM SIGMOD workshop on information quality in information systems (IQIS), Paris, France, pp 59-67
9. Breunig M, Kriegel H, Ng R, Sander J (2000) LOF: Identifying density-based local outliers. In: Proceedings of 2000 ACM SIGMOD conference, Dallas, TX, USA, pp 93-104
10. Brodie ML (1980) Data quality in information systems. Inform Manage 3:245-258
11. Celko J, McDonald J (1995) Don't warehouse dirty data. Datamation 41(18)
12. Chaudhuri S, Ganjam K, Ganti V, Motwani R (2003) Robust and efficient fuzzy match for online data cleaning. In: Proceedings of the 2003 ACM SIGMOD international conference on management of data, San Diego, CA, USA, pp 313-324
13. Cui Y, Widom J (2001) Lineage tracing for general data warehouse transformation. In: Proceedings of the 27th international conference on very large data bases (VLDB), Roma, Italy, September 11-14, pp 471-480
14. Dasu T, Johnson T (2003) Exploratory data mining and data cleaning. Wiley, New York
15. Dasu T, Johnson T, Muthukrishnan S, Shkapenyuk V (2002) Mining database structure or, how to build a data quality browser. In: Proceedings of the 2002 ACM SIGMOD international conference on management of data, Madison, WI, USA, pp 240-251
16. De Giacomo G, Lembo D, Lenzerini M, Rosati R (2004) Tackling inconsistencies in data integration through source preferences. In: Proceedings of the 1st ACM SIGMOD workshop on information quality in information systems (IQIS), Paris, France, pp 27-34
17. Delen G, Rijsenbrij D (1992) The specification, engineering and measurement of information systems quality. J Softw Syst 17:205-217
18. Elfeky MG, Verykios VS, Elmagarmid AK (2002) Tailor: A record linkage toolbox. In: Proceedings of the 19th international conference on data engineering (ICDE), San Jose, CA, USA, pp 1-28
19. English L (1998) Improving data warehouse and business information quality. Wiley, New York
20. Fan K, Lu H, Madnick S, Cheung D (2001) Discovering and reconciling value conflicts for numerical data integration. Inform Syst 26(8):235-656
21. Fellegi IP, Sunter AB (1969) A theory for record linkage. J Am Stat Assoc 64:1183-1210
22. Fox C, Levitin A, Redman T (1994) The notion of data and its quality dimensions. Information Processing and Management 30(1)
23. Gravano L, Ipeirotis PG, Koudas N, Srivastava D (2003) Text joins in an RDBMS for web data integration. In: Proceedings of the 12th international world wide web conference (WWW), Budapest, Hungary, pp 90-101
24. Hernandez M, Stolfo S (1998) Real-world data is dirty: Data cleansing and the merge/purge problem. Data Min Knowl Discov 2(1):9-37
25. Hou WC, Zhang Z (1995) Enhancing database correctness: A statistical approach. In: Proceedings of the 1995 ACM SIGMOD international conference on management of data, San Jose, CA, USA
26. Huang K, Lee Y, Wang R (1999) Quality information and knowledge management. Prentice Hall, New Jersey
27. Jarke M, Jeusfeld MA, Quix C, Vassiliadis P (1998) Architecture and quality in data warehouses. In: Proceedings of the 10th international conference on advanced information systems engineering (CAiSE), Pisa, Italy, pp 93-113
28. Johnson T, Dasu T (1998) Comparing massive high-dimensional data sets. In: Proceedings of the 4th international conference KDD, New York City, New York, USA, pp 229-233
29. Kahn B, Strong D, Wang R (2002) Information quality benchmark: Product and service performance. Com. ACM 45(4):184-192
30. Knorr E, Ng R (1998) Algorithms for mining distance-based outliers in large datasets. In: Proceedings of the 24th international conference on very large data bases (VLDB), New York City, USA, pp 392-403
31. Lavrač N, Flach PA, Zupan B (1999) Rule evaluation measures: A unifying view. In: Proceedings of the international workshop on inductive logic programming (ILP), Bled, Slovenia, pp 174-185
32. Liepins G, Uppuluri V (1990) Data quality control: Theory and pragmatics. Marcel Dekker, New York
33. Lim L, Srivastava J, Prabhakar S, Richardson J (1993) Entity identification in database integration. In: Proceedings of the 9th international conference on data engineering (ICDE), Vienna, Austria, pp 294-301
34. Little RJ, Rubin DB (1987) Statistical analysis with missing data. Wiley, New York
35. Liu L, Chi L (2002) Evolutionary data quality. In: Proceedings of the 7th international conference on information quality (IQ), MIT, Cambridge, USA
36. McCallum A, Nigam K, Ungar LH (2000) Efficient clustering of high-dimensional data sets with application to reference matching. In: Proceedings of the 6th ACM SIGKDD conference on knowledge discovery and data mining (KDD), Boston, MA, USA, pp 169-178
37. Mihaila GA, Raschid L, Vidal M (2000) Using quality of data metadata for source selection and ranking. In: Proceedings of the 3rd international WebDB workshop, Dallas, TX, USA, pp 93-98
38. Missier P, Batini C (2003) A multidimensional model for information quality in CIS. In: Proceedings of the 8th international conference on information quality (IQ), MIT, Cambridge, MA, USA
39. Monge A (2000) Matching algorithms within a duplicate detection system. IEEE Data Eng Bull 23(4):14-20
40. Müller H, Leser U, Freytag JC (2004) Mining for patterns in contradictory data. In: Proceedings of the 1st ACM SIGMOD workshop on information quality in information systems (IQIS) in conjunction with ACM PODS/SIGMOD, Paris, France, pp 51-58
41. Naumann F, Leser U, Freytag J (1999) Quality-driven integration of heterogeneous information systems. In: Proceedings of the 25th international conference on very large data bases (VLDB), Edinburgh, Scotland, pp 447-458
42. Naumann F (2002) Quality-driven query answering for integrated information systems. LNCS 2261, Springer, Berlin Heidelberg New York
43. Pasula H, Marthi B, Milch B, Russell S, Shpitser I (2003) Identity uncertainty and citation matching. In: Proceedings of the international conference advances in neural information processing systems (NIPS), Vancouver, British Colombia, pp 1401-1408
44. Pearson RK (2002) Data mining in face of contaminated and incomplete records. In: Proceedings of SIAM international conference on data mining
45. Perner P (2002) Data mining on multimedia. LNCS 2558, Springer, Berlin Heidelberg New York
46. Piattini M, Genero M, Calero C, Polo C, Ruiz F (2000) Database quality. Chapter 14: Advanced database technology and design. Artech House, Norwood, MA, pp 485-509
47. Piattini, M, Calero C, Genero M (eds)(2002) Information and database quality. The Kluwer International Series on Advances in Database Systems, 25
48. Pyle D (1999) Data preparation for data mining. Morgan Kaufmann, San Mateo, CA
49. Rahm E, Do H (2000) Data cleaning: Problems and current approaches. IEEE Data Eng Bull 23(4):3-13
50. Raman V, Hellerstein JM (2001) Potter's wheel: An interactive data cleaning system. In: Proceedings of the 26th international conference on very large data bases (VLDB), Roma, Italy, pp 381-390
51. Redman T (2001) Data quality: The field guide. Digital Press, Elsevier
52. Rothenberg J (1996) Metadata to support data quality and longevity. In: Proceedings of the 1st IEEE metadata conference, Silver Spring, MD
53. Santis LD, Scannapieco M, Catarci T (2003) Trusting data quality in cooperative information systems. In: Proceedings of the international conference on cooperative information systems (CoopIS), Catania, Sicily, Italy, pp 354-369
54. Scannapieco M, Pernici B, Pierce E (2004) IP-UML: A methodology for quality improvement based on IP-MAP and UML. Advances in Management Information Systems-Information Quality Monograph (AMIS-IQ), Sharpe
55. Schafer JL (1997) Analysis of incomplete multivariate data. Chapman & Hall, London
56. Schlimmer J (1991) Learning determinations and checking databases. In: Proceedings of AAAI workshop on knowledge discovery in databases, AAAI-1991 Anaheim California
57. Tan P-N, Kumar V, Srivastava J (2002) Selecting the right interestingness measure for association patterns. In: Proceedings of the 8th ACM SIGKDD conference on knowledge discovery and data mining (KDD), Edmonton, Canada, pp 32-41
58. Theodoratos D, Bouzeghoub M (2001) Data currency quality satisfaction in the design of a data warehouse. Special Issue on design and management of data warehouses. Int J Coop Inf Syst 10(3):299-326
59. Vassiliadis P, Bouzeghoub M, Quix C (1999) Towards quality-oriented data warehouse usage and evolution. In: Proceedings of the 11th international conference on advanced information systems engineering (CAiSE), Heidelberg, Germany, pp 164-179
60. Vassiliadis P, Simitsis A, Georgantas P, Terrovitis M (2003) A framework for the design of ETL scenarios. In: Proceedings of the 15th international conference on advanced information systems engineering (CAiSE), Klagenfurt, Austria, pp 520-535
61. Vassiliadis P (2000) Data warehouse modeling and quality issues. PhD thesis, Technical University of Athens, Greece
62. Wang R, Kon HB, Madnick SE (1993) Data quality requirements analysis and modeling. In: Proceedings of the 9th international conference on data engineering (ICDE), Vienna, Austria, pp 670-677
63. Wang R, Storey V, Firth C (1995) A framework for analysis of data quality research. IEEE Trans Knowl Data Eng (TDKE) 7(4):670-677
64. Wang R (1998) A product perspective on total data quality management. Com. ACM 41(2):58-65
65. Wang R (2002) Journey to data quality, vol 23 of Advances in database systems. Kluwer, Boston, MA, USA
66. Wang K, Zhou S, Yang Q, Yeung JMS (2005) Mining customer value: From association rules to direct marketing. J Data Min Knowl Discov
67. Weis M, Naumann F (2004) Detecting duplicate objects in XML documents. In: Proceedings of the 1st international ACM SIGMOD workshop on information quality in information systems (IQIS) in conjunction with ACM PODS/SIGMOD, Paris, France, pp 10-19
68. Winkler WE (2004) Methods for evaluating and creating data quality. Inf Syst 29(7)