HOS-Miner

Proceedings 2004 VLDB Conference: The 30th International Conference on Very Large Databases (VLDB)

Volumn , Issue , 2004, Pages 1265-1268

  Zhang, Ji ^a   Lou, Meng ^a   Wang, Hai ^a   Ling, Tok Wang ^b  

^a UNIVERSITY OF TORONTO   (Canada)

^b NATIONAL UNIVERSITY OF SINGAPORE   (Singapore)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 85053220546     PISSN: None     EISSN: None     Source Type: Book    
DOI: 10.1016/B978-012088469-8.50123-6     Document Type: Chapter

References (8)

1. C.C. Aggarwal and P.S. Yu (2001) Outlier Detection in High Dimensional Data. Proc. ACM SIGMOD'00 Santa Barbara, California
2. S. Berchtold, D.A. Keim and H. Kriegel (1996) The X-tree: An Index Structure for High-Dimensional Data. Proc. VLDB'96 Mumbai, India
3. M. Breuning, H-P Kriegel, R. Ng and J. Sander (2000) LOF: Identifying Density-Based Local Outliers. Proc. ACM SIGMOD'00 Dallas, Texas
4. W. Jin, A.K.H. Tung and J. Han (August, 2001) Finding Top n Local Outliers in Large Database. Proc. SIGKDD'01 San Francisco, CA
5. E.M. Knorr and R.T. Ng (August 1998) Algorithms for Mining Distance-based Outliers in Large Dataset. Proc. VLDB'98 New York, NY 392-403.
6. E.M. Knorr and R.T. Ng (1999) Finding Intentional Knowledge of Distance-based Outliers. Proc. VLDB'99 Edinburg, Scotland 211-222.
7. S. Papadimitriou, H. Kitagawa, P.B. Gibbons and C. Faloutsos (2003) LOCI: Fast Outlier Detection Using the Local Correlation Integral. Proc. ICDE'03 Bangalore, India 315.
8. S. Ramaswamy, R. Rastogi and S. Kyuseok (2000) Efficient Algorithms for Mining Outliers from Large Data Sets. Proc. ACM SIGMOD'00 Dallas, Texas