메뉴 건너뛰기




Volumn 12, Issue 6, 2006, Pages 627-653

Data mining methods for discovering interesting exceptions from an unsupervised table

Author keywords

Data mining; Exception; Instance; Interestingness; Pattern; Rule; Unexpectedness

Indexed keywords


EID: 33746820611     PISSN: 0958695X     EISSN: 09486968     Source Type: Journal    
DOI: None     Document Type: Article
Times cited : (25)

References (82)
  • 2
    • 0040154165 scopus 로고    scopus 로고
    • Re-designing distance functions and distance-based applications for high dimensional data
    • [Aggarwal 2001]
    • [Aggarwal 2001] Aggarwal, C. C.: "Re-designing Distance Functions and Distance-Based Applications for High Dimensional Data", SIGMOD Record. 30, 1 (2001), 13-18.
    • (2001) SIGMOD Record , vol.30 , Issue.1 , pp. 13-18
    • Aggarwal, C.C.1
  • 11
    • 33745834241 scopus 로고    scopus 로고
    • [Blake 1999], Univ. of Calif. Irvine, Dept. Information and CS (current May 5)
    • [Blake 1999] Blake, C., Merz, C.J., Keogh, E.: "UCI Repository of Machine Learning Databases", http://www.ics.uci.edu/~mlearn/MLRepository. ktml, Univ. of Calif. Irvine, Dept. Information and CS (current May 5, 1999).
    • (1999) UCI Repository of Machine Learning Databases
    • Blake, C.1    Merz, C.J.2    Keogh, E.3
  • 14
    • 0010852727 scopus 로고    scopus 로고
    • Unsupervised neural network approach to profiling the behavior of mobile phone users for use in fraud detection
    • [Burge and Shawe-Taylor 2001]
    • [Burge and Shawe-Taylor 2001] Burge, P. and Shawe-Taylor, J.: "Unsupervised Neural Network Approach to Profiling the Behavior of Mobile Phone Users for Use in Fraud Detection", J. Parallel and Distributed Computing, 61 (2001), 915-925.
    • (2001) J. Parallel and Distributed Computing , vol.61 , pp. 915-925
    • Burge, P.1    Shawe-Taylor, J.2
  • 15
    • 0002758989 scopus 로고    scopus 로고
    • Mining Surprising Patterns using temporal description Length
    • [Chakrabarti et al. 1998]
    • [Chakrabarti et al. 1998] Chakrabarti, S., Sarawagi, S., Dom., B.: "Mining Surprising Patterns using temporal description Length", Proc. 24th VLDB Conf. (1998), 606-617.
    • (1998) Proc. 24th VLDB Conf. , pp. 606-617
    • Chakrabarti, S.1    Sarawagi, S.2    Dom, B.3
  • 16
    • 85083464467 scopus 로고    scopus 로고
    • Toward scalable learning with non-uniform class and cost distributions: A case study in credit card fraud detection
    • [Chan and Stolfo 1998]
    • [Chan and Stolfo 1998] Chan, P. K., Stolfo, S. J.: "Toward Scalable Learning with Non-Uniform Class and Cost Distributions: A Case Study in Credit Card Fraud Detection" Proc. Fourth Int'l Conf. on Knowledge Discovery and Data Mining (KDD), (1998), 164-168.
    • (1998) Proc. Fourth Int'l Conf. on Knowledge Discovery and Data Mining (KDD) , pp. 164-168
    • Chan, P.K.1    Stolfo, S.J.2
  • 21
    • 0002433547 scopus 로고    scopus 로고
    • From data mining to knowledge discovery: An overview
    • [Fayyad et al. 1996], eds. U. M. Fayyad et al., AAAI/MIT Press, Menlo Park, Calif.
    • [Fayyad et al. 1996] Fayyad, U. M., Piatetsky-Shapiro, G., Smyth, P.: "From Data Mining to Knowledge Discovery: An Overview", Advances in Knowledge Discovery and Data Mining, eds. U. M. Fayyad et al., AAAI/MIT Press, Menlo Park, Calif. (1996), 1-34.
    • (1996) Advances in Knowledge Discovery and Data Mining , pp. 1-34
    • Fayyad, U.M.1    Piatetsky-Shapiro, G.2    Smyth, P.3
  • 22
    • 0013113240 scopus 로고    scopus 로고
    • Adaptive fraud detection
    • [Fawcett and Provost 1997]
    • [Fawcett and Provost 1997] Fawcett, T., Provost, F.: "Adaptive Fraud Detection", Data Mining and Knowledge Discovery. 1, 3 (1997), 291-316.
    • (1997) Data Mining and Knowledge Discovery , vol.1 , Issue.3 , pp. 291-316
    • Fawcett, T.1    Provost, F.2
  • 23
    • 0001790815 scopus 로고
    • Knowledge discovery in databases: An overview
    • [Frawley et al. 1991], AAAI/MIT Press, Menlo Park, Calif.
    • [Frawley et al. 1991] Frawley, W. J., Piatetsky-Shapiro, G., Matheus, C. J.: "Knowledge Discovery in Databases: An Overview", Knowledge Discovery in Databases, AAAI/MIT Press, Menlo Park, Calif. (1991), 1-27.
    • (1991) Knowledge Discovery in Databases , pp. 1-27
    • Frawley, W.J.1    Piatetsky-Shapiro, G.2    Matheus, C.J.3
  • 24
    • 0011957932 scopus 로고    scopus 로고
    • Descriptive induction through subgroup discovery: A case study in a medical domain
    • [Gamberger and Lavrač 2002a]
    • [Gamberger and Lavrač 2002a] Gamberger, D., Lavrač, N.: "Descriptive Induction through Subgroup Discovery: A Case Study in a Medical Domain", Proc. Nineteenth Int'l Conf. on Machine Learning (ICML) (2002), 163-170.
    • (2002) Proc. Nineteenth Int'l Conf. on Machine Learning (ICML) , pp. 163-170
    • Gamberger, D.1    Lavrač, N.2
  • 25
  • 29
    • 0009985887 scopus 로고
    • A support system for interpreting statistical data
    • [Hoschka and Klösgen 1991], AAAI/MIT Press, Menlo Park, Calif.
    • [Hoschka and Klösgen 1991] Hoschka, P., Klösgen, W.: "A Support System for Interpreting Statistical Data", Knowledge Discovery in Databases, AAAI/MIT Press, Menlo Park, Calif. (1991), 325-345.
    • (1991) Knowledge Discovery in Databases , pp. 325-345
    • Hoschka, P.1    Klösgen, W.2
  • 35
    • 0002192370 scopus 로고    scopus 로고
    • Explora,: A multipattern and multistrategy discovery approach
    • [Klösgen 1996], eds. U. M. Fayyad et al., AAAI/MIT Press, Menlo Park, Calif.
    • [Klösgen 1996] Klösgen, W.: "Explora,: A Multipattern and Multistrategy Discovery Approach", Advances in Knowledge Discovery and Data Mining, eds. U. M. Fayyad et al., AAAI/MIT Press, Menlo Park, Calif. (1996), 249-271.
    • (1996) Advances in Knowledge Discovery and Data Mining , pp. 249-271
    • Klösgen, W.1
  • 38
    • 0034133513 scopus 로고    scopus 로고
    • Distance-based outliers: Algorithms and applications
    • [Knorr et al. 2000]
    • [Knorr et al. 2000] Knorr, E. M., Ng, R. T., Tucakov, V.: "Distance-Based Outliers: Algorithms and Applications", VLDB J., 8, 3-4 (2000), 237-253.
    • (2000) VLDB J. , vol.8 , Issue.3-4 , pp. 237-253
    • Knorr, E.M.1    Ng, R.T.2    Tucakov, V.3
  • 41
    • 0033333282 scopus 로고    scopus 로고
    • Finding interesting patterns using user expectations
    • [Liu et al. 1999a]
    • [Liu et al. 1999a] Liu, B. et al.: "Finding Interesting Patterns Using User Expectations", IEEE Trans. Knowledge and Data Eng., 11, 6 (1999), 817-832.
    • (1999) IEEE Trans. Knowledge and Data Eng. , vol.11 , Issue.6 , pp. 817-832
    • Liu, B.1
  • 45
    • 37349044608 scopus 로고
    • Circumscription - A form of nonmonotonic reasoning
    • [McCarthy 1980]
    • [McCarthy 1980] J. McCarthy: "Circumscription - a form of nonmonotonic reasoning", Artificial Intelligence, 13, (1980), 27-39.
    • (1980) Artificial Intelligence , vol.13 , pp. 27-39
    • McCarthy, J.1
  • 46
    • 0002337827 scopus 로고    scopus 로고
    • Machine learning and data mining
    • [Mitchell 1999]
    • [Mitchell 1999] T.M. Mitchell, Machine Learning and Data Mining, CACM 42 (1999), 31-36.
    • (1999) CACM , vol.42 , pp. 31-36
    • Mitchell, T.M.1
  • 48
    • 84956861964 scopus 로고    scopus 로고
    • Rule induction in cascade model based on sum of squares decomposition
    • [Okada 1999], Springer-Verlag
    • [Okada 1999] Okada, T.: "Rule Induction in Cascade Model Based on Sum of Squares Decomposition", Principles of Data Mining and Knowledge Discovery (PKDD). LNAI1704, Springer-Verlag (1999), 468-474.
    • (1999) Principles of Data Mining and Knowledge Discovery (PKDD). LNAI1704 , pp. 468-474
    • Okada, T.1
  • 57
    • 0030380606 scopus 로고    scopus 로고
    • What makes patterns interesting in knowledge discovery systems
    • [Silberschatz and Tuzhilin 1996]
    • [Silberschatz and Tuzhilin 1996] Silberschatz, A., Tuzhilin, A.: "What Makes Patterns Interesting in Knowledge Discovery Systems", IEEE Trans. Knowledge and Data Eng., 8, 6 (1996), 970-974.
    • (1996) IEEE Trans. Knowledge and Data Eng. , vol.8 , Issue.6 , pp. 970-974
    • Silberschatz, A.1    Tuzhilin, A.2
  • 58
    • 0026902042 scopus 로고
    • An information theoretic approach to rule induction from databases
    • [Smyth and Goodman 1992]
    • [Smyth and Goodman 1992] Smyth, P., Goodman, R. M.: "An Information Theoretic Approach to Rule Induction from Databases", IEEE Trans. Knowledge and Data Eng., 4 (1992), 301-316.
    • (1992) IEEE Trans. Knowledge and Data Eng. , vol.4 , pp. 301-316
    • Smyth, P.1    Goodman, R.M.2
  • 59
    • 0035034182 scopus 로고    scopus 로고
    • Visualization and interactive analysis of blood parameters with InfoZoom
    • [Spenke 2001]
    • [Spenke 2001] Spenke, M.: "Visualization and Interactive Analysis of Blood Parameters with InfoZoom", Artificial Intelligence in Medicine, 22, 2 (2001), 159-172.
    • (2001) Artificial Intelligence in Medicine , vol.22 , Issue.2 , pp. 159-172
    • Spenke, M.1
  • 60
    • 33746832799 scopus 로고    scopus 로고
    • Instance selection based on support vector machine for knowledge discovery in medical database
    • [Sugaya et al. 2001], H. Liu and H. Motoda (eds.), Kluwer, Norwell, Mass.
    • [Sugaya et al. 2001] Sugaya, S., Suzuki, E., Tsumoto, S.: "Instance Selection Based on Support Vector Machine for Knowledge Discovery in Medical Database", Instance Selection and Construction for Data Mining, H. Liu and H. Motoda (eds.), Kluwer, Norwell, Mass. (2001), 395-412.
    • (2001) Instance Selection and Construction for Data Mining , pp. 395-412
    • Sugaya, S.1    Suzuki, E.2    Tsumoto, S.3
  • 61
    • 84920878139 scopus 로고    scopus 로고
    • Exceptional knowledge discovery in databases based on information theory
    • [Suzuki and Shimura 1996], AAAI Press, Menlo Park, Calif.
    • [Suzuki and Shimura 1996] Suzuki, E., Shimura, M.: "Exceptional Knowledge Discovery in Databases Based on Information Theory", Proc. Second Int'l Conf. Knowledge Discovery and Data Mining (KDD), AAAI Press, Menlo Park, Calif. (1996), 275-278.
    • (1996) Proc. Second Int'l Conf. Knowledge Discovery and Data Mining (KDD) , pp. 275-278
    • Suzuki, E.1    Shimura, M.2
  • 63
    • 84964943935 scopus 로고    scopus 로고
    • Autonomous discovery of reliable exception rules
    • [Suzuki 1997], AAAI Press, Menlo Park, Calif.
    • [Suzuki 1997] Suzuki, E.: "Autonomous Discovery of Reliable Exception Rules", Proc. Third Int'l Conf. Knowledge Discovery and Data Mining (KDD), AAAI Press, Menlo Park, Calif. (1997), 259-262.
    • (1997) Proc. Third Int'l Conf. Knowledge Discovery and Data Mining (KDD) , pp. 259-262
    • Suzuki, E.1
  • 64
    • 84947703686 scopus 로고    scopus 로고
    • Discovery of surprising exception rules based on intensity of implication
    • [Suzuki and Kodratoff 1998], Springer
    • [Suzuki and Kodratoff 1998] Suzuki, E., Kodratoff, Y.: "Discovery of Surprising Exception Rules Based on Intensity of Implication", Principles of Data Mining and Knowledge Discovery, LNAI 1510 (PKDD), Springer (1998), 10-18.
    • (1998) Principles of Data Mining and Knowledge Discovery, LNAI 1510 (PKDD) , pp. 10-18
    • Suzuki, E.1    Kodratoff, Y.2
  • 65
    • 33645800278 scopus 로고    scopus 로고
    • Evaluating hypothesis-driven exception-rule discovery with medical data sets
    • [Suzuki and Tsumoto 2000], Springer, Berlin
    • [Suzuki and Tsumoto 2000] Suzuki, E., Tsumoto, S.: "Evaluating Hypothesis-Driven Exception-Rule Discovery with Medical Data Sets", Knowledge Discovery and Data Mining, LNAI 1805 (PAKDD), Springer, Berlin (2000), 208-211.
    • (2000) Knowledge Discovery and Data Mining, LNAI 1805 (PAKDD) , pp. 208-211
    • Suzuki, E.1    Tsumoto, S.2
  • 67
    • 0012017165 scopus 로고    scopus 로고
    • Mining bacterial test data with scheduled discovery of exception rules
    • [Suzuki 2000b], Kyoto, Japan
    • [Suzuki 2000b] Suzuki, E.: "Mining Bacterial Test Data with Scheduled Discovery of Exception Rules", Proc. Int'l Workshop of KDD Challenge on Real-world Data (KDD Challenge), Kyoto, Japan (2000), 34-40.
    • (2000) Proc. Int'l Workshop of KDD Challenge on Real-world Data (KDD Challenge) , pp. 34-40
    • Suzuki, E.1
  • 71
    • 21844465455 scopus 로고    scopus 로고
    • Evaluation scheme for exception rule/group discovery
    • [Suzuki 2004b], Springer, Berlin
    • [Suzuki 2004b] Suzuki, E.: "Evaluation Scheme for Exception Rule/Group Discovery", Intelligent Technologies for Information Analysis, Springer, Berlin (2004), 89-108.
    • (2004) Intelligent Technologies for Information Analysis , pp. 89-108
    • Suzuki, E.1
  • 72
    • 21844457136 scopus 로고    scopus 로고
    • Unified algorithm for undirected discovery of exception rules
    • [Suzuki and Zytkow 2005]
    • [Suzuki and Zytkow 2005] Suzuki, E., Zytkow, J. M.: "Unified Algorithm for Undirected Discovery of Exception Rules", International Journal of Intelligent Systems, 20, 7 (2005), 673-691.
    • (2005) International Journal of Intelligent Systems , vol.20 , Issue.7 , pp. 673-691
    • Suzuki, E.1    Zytkow, J.M.2
  • 74
    • 34548792706 scopus 로고    scopus 로고
    • An algorithm for multi-relational discovery of subgroups
    • [Wrobel 1997], Springer-Verlag
    • [Wrobel 1997] Wrobel, S.: "An Algorithm for Multi-relational Discovery of Subgroups", Principles of Data Mining and Knowledge Discovery (PKDD), LNCS 1263, Springer-Verlag (1997), 78-87.
    • (1997) Principles of Data Mining and Knowledge Discovery (PKDD), LNCS , vol.1263 , pp. 78-87
    • Wrobel, S.1
  • 75
    • 1942451954 scopus 로고    scopus 로고
    • Decision-tree induction from time-series data based on a standard-example split test
    • [Yamada, et al. 2003], (erratum http://www.slab.dnj.ynu.ac.jp/ erratumicml2003.pdf)
    • [Yamada, et al. 2003] Yamada, Y., Suzuki, E., Yokoi, H., Takabayashi, K.: "Decision-tree Induction from Time-series Data Based on a Standard-example Split Test", Proc. Twentieth International Conference on Machine Learning (ICML), (erratum http://www.slab.dnj.ynu.ac.jp/erratumicml2003.pdf) (2003), 840-847.
    • (2003) Proc. Twentieth International Conference on Machine Learning (ICML) , pp. 840-847
    • Yamada, Y.1    Suzuki, E.2    Yokoi, H.3    Takabayashi, K.4


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.