SCOPUS 정보 검색 플랫폼

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 6323 LNAI, Issue PART 3, 2010, Pages 607-610

SOREX: Subspace outlier ranking exploration toolkit

(6) Müller, Emmanuel a Schiffer, Matthias a Gerwert, Patrick a Hannen, Matthias a Jansen, Timm a Seidl, Thomas a

a RWTH AACHEN UNIVERSITY (Germany)

Author keywords

[No Author keywords available]

Indexed keywords

DATA ANALYSIS; DESCRIPTIVE INFORMATION; KNOWLEDGE EXTRACTION; OPEN SOURCE FRAMEWORKS; OUTLIER MINING; RANKING METHODS; RESEARCH AREAS; SUBSPACE PROJECTION;

DATA REDUCTION; LEARNING SYSTEMS;

RESEARCH;

EID: 77958047461 PISSN: 03029743 EISSN: 16113349 Source Type: Book Series
DOI: 10.1007/978-3-642-15939-8_44 Document Type: Conference Paper

Times cited : (12)

References (9)

1
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- Outlier detection for high dimensional data
- Aggarwal, C.C., Yu, P.S.: Outlier detection for high dimensional data. In: SIGMOD, pp. 37-46 (2001)
- (2001) SIGMOD , pp. 37-46
- Aggarwal, C.C.¹ Yu, P.S.²

2
- 32344440279
- Feature bagging for outlier detection
- Lazarevic, A., Kumar, V.: Feature bagging for outlier detection. In: KDD, pp. 157-166 (2005)
- (2005) KDD , pp. 157-166
- Lazarevic, A.¹ Kumar, V.²

3
- 50249129339
- Outrank: Ranking outliers in high dimensional data
- Müller, E., Assent, I., Steinhausen, U., Seidl, T.: Outrank: Ranking outliers in high dimensional data. In: DBRank Workshop at ICDE, pp. 600-603 (2008)
- (2008) DBRank Workshop at ICDE , pp. 600-603
- Müller, E.¹ Assent, I.² Steinhausen, U.³ Seidl, T.⁴

4
- 67650661596
- Outlier detection in axis-parallel subspaces of high dimensional data
- Kriegel, H.P., Schubert, E., Zimek, A., Kr̈oger, P.: Outlier detection in axis-parallel subspaces of high dimensional data. In: PAKDD, pp. 831-838 (2009)
- (2009) PAKDD , pp. 831-838
- Kriegel, H.P.¹ Schubert, E.² Zimek, A.³ Kr̈oger, P.⁴

5
- 0039253819
- LOF: Identifying density-based local outliers
- Breunig, M., Kriegel, H.P., Ng, R., Sander, J.: LOF: identifying density-based local outliers. In: SIGMOD, pp. 93-104 (2000)
- (2000) SIGMOD , pp. 93-104
- Breunig, M.¹ Kriegel, H.P.² Ng, R.³ Sander, J.⁴

6
- 65449145220
- Angle-based outlier detection in high-dimensional data
- Kriegel, H.P., Schubert, M., Zimek, A.: Angle-based outlier detection in high-dimensional data. In: KDD, pp. 444-452 (2008)
- (2008) KDD , pp. 444-452
- Kriegel, H.P.¹ Schubert, M.² Zimek, A.³

7
- 65449157709
- Morpheus: Interactive exploration ofsubspace clustering
- Müller, E., Assent, I., Krieger, R., Jansen, T., Seidl, T.: Morpheus: Interactive exploration ofsubspace clustering. In: KDD, pp. 1089-1092 (2008)
- (2008) KDD , pp. 1089-1092
- Müller, E.¹ Assent, I.² Krieger, R.³ Jansen, T.⁴ Seidl, T.⁵

8
- 84865086248
- Evaluating clustering in subspace projections of high dimensional data
- Müller, E., Günnemann, S., Assent, I., Seidl, T.: Evaluating clustering in subspace projections of high dimensional data. In: VLDB, pp. 1270-1281 (2009)
- (2009) VLDB , pp. 1270-1281
- Müller, E.¹ Günnemann, S.² Assent, I.³ Seidl, T.⁴

9
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- VISA: Visual subspace clustering anal-ysis
- Assent, I., Krieger, R., Müller, E., Seidl, T.: VISA: Visual subspace clustering anal-ysis. ACM SIGKDD Explorations 9(2), 5-12 (2007)
- (2007) ACM SIGKDD Explorations , vol.9 , Issue.2 , pp. 5-12
- Assent, I.¹ Krieger, R.² Müller, E.³ Seidl, T.⁴

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