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Conference Paper: Enhancing Effectiveness of Outlier Detections for Low Density Patterns
| Title | Enhancing Effectiveness of Outlier Detections for Low Density Patterns |
|---|---|
| Authors | |
| Issue Date | 2002 |
| Publisher | Springer. |
| Citation | Advances in knowledge discovery and data mining 6th Pacific-Asia conference (PAKDD 2002), Taipei, Taiwan, 6-8 May 2002, p. 535-548 How to Cite? |
| Abstract | Outlier detection is concerned with discovering exceptional behaviors of objects in data sets.It is becoming a growingly useful tool in applications such as credit card fraud detection, discovering criminal behaviors in e-commerce, identifying computer intrusion, detecting health problems, etc. In this paper, we introduce a connectivity-based outlier factor (COF) scheme that improves the effectiveness of an existing local outlier factor (LOF) scheme when a pattern itself has similar neighbourhood density as an outlier. We give theoretical and empirical analysis to demonstrate the improvement in effectiveness and the capability of the COF scheme in comparison with the LOF scheme. |
| Persistent Identifier | http://hdl.handle.net/10722/93395 |
| ISBN |
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Tang, J | en_HK |
| dc.contributor.author | Chen, Z | en_HK |
| dc.contributor.author | Fu, A | en_HK |
| dc.contributor.author | Cheung, DWL | en_HK |
| dc.date.accessioned | 2010-09-25T14:59:47Z | - |
| dc.date.available | 2010-09-25T14:59:47Z | - |
| dc.date.issued | 2002 | en_HK |
| dc.identifier.citation | Advances in knowledge discovery and data mining 6th Pacific-Asia conference (PAKDD 2002), Taipei, Taiwan, 6-8 May 2002, p. 535-548 | - |
| dc.identifier.isbn | 3-540-43704-5 | - |
| dc.identifier.uri | http://hdl.handle.net/10722/93395 | - |
| dc.description.abstract | Outlier detection is concerned with discovering exceptional behaviors of objects in data sets.It is becoming a growingly useful tool in applications such as credit card fraud detection, discovering criminal behaviors in e-commerce, identifying computer intrusion, detecting health problems, etc. In this paper, we introduce a connectivity-based outlier factor (COF) scheme that improves the effectiveness of an existing local outlier factor (LOF) scheme when a pattern itself has similar neighbourhood density as an outlier. We give theoretical and empirical analysis to demonstrate the improvement in effectiveness and the capability of the COF scheme in comparison with the LOF scheme. | - |
| dc.language | eng | en_HK |
| dc.publisher | Springer. | - |
| dc.relation.ispartof | Advances in knowledge discovery and data mining | en_HK |
| dc.title | Enhancing Effectiveness of Outlier Detections for Low Density Patterns | en_HK |
| dc.type | Conference_Paper | en_HK |
| dc.identifier.email | Cheung, DWL: dcheung@cs.hku.hk | en_HK |
| dc.identifier.authority | Cheung, DWL=rp00101 | en_HK |
| dc.identifier.hkuros | 71003 | en_HK |