by Chiu Lai Mei. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2003. / Includes bibliographical references (leaves 142-149). / Abstracts in English and Chinese. / Abstract --- p.ii / Acknowledgement --- p.vi / Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- Outlier Analysis --- p.2 / Chapter 1.2 --- Problem Statement --- p.4 / Chapter 1.2.1 --- Binary Property of Outlier --- p.4 / Chapter 1.2.2 --- Overlapping Clusters with Different Densities --- p.4 / Chapter 1.2.3 --- Large Datasets --- p.5 / Chapter 1.2.4 --- High Dimensional Datasets --- p.6 / Chapter 1.3 --- Contributions --- p.8 / Chapter 2 --- Related Work in Outlier Detection --- p.10 / Chapter 2.1 --- Outlier Detection --- p.11 / Chapter 2.1.1 --- Clustering-Based Methods --- p.11 / Chapter 2.1.2 --- Distance-Based Methods --- p.14 / Chapter 2.1.3 --- Density-Based Methods --- p.18 / Chapter 2.1.4 --- Deviation-Based Methods --- p.22 / Chapter 2.2 --- Breakthrough Outlier Notion: Degree of Outlier-ness --- p.25 / Chapter 2.2.1 --- LOF: Local Outlier Factor --- p.26 / Chapter 2.2.2 --- Definitions --- p.26 / Chapter 2.2.3 --- Properties --- p.29 / Chapter 2.2.4 --- Algorithm --- p.30 / Chapter 2.2.5 --- Time Complexity --- p.31 / Chapter 2.2.6 --- LOF of High Dimensional Data --- p.31 / Chapter 3 --- LOF': Formula with Intuitive Meaning --- p.33 / Chapter 3.1 --- Definition of LOF' --- p.33 / Chapter 3.2 --- Properties --- p.34 / Chapter 3.3 --- Time Complexity --- p.37 / Chapter 4 --- "LOF"" for Detecting Small Groups of Outliers" --- p.39 / Chapter 4.1 --- "Definition of LOF"" " --- p.40 / Chapter 4.2 --- Properties --- p.41 / Chapter 4.3 --- Time Complexity --- p.44 / Chapter 5 --- GridLOF for Pruning Reasonable Portions from Datasets --- p.46 / Chapter 5.1 --- GridLOF Algorithm --- p.47 / Chapter 5.2 --- Determine Values of Input Parameters --- p.51 / Chapter 5.2.1 --- Number of Intervals w --- p.51 / Chapter 5.2.2 --- Threshold Value σ --- p.52 / Chapter 5.3 --- Advantages --- p.53 / Chapter 5.4 --- Time Complexity --- p.55 / Chapter 6 --- SOF: Efficient Outlier Detection for High Dimensional Data --- p.57 / Chapter 6.1 --- Motivation --- p.57 / Chapter 6.2 --- Notations and Definitions --- p.59 / Chapter 6.3 --- SOF: Subspace Outlier Factor --- p.62 / Chapter 6.3.1 --- Formal Definition of SOF --- p.62 / Chapter 6.3.2 --- Properties of SOF --- p.67 / Chapter 6.4 --- SOF-Algorithm: the Overall Framework --- p.73 / Chapter 6.5 --- Identify Associated Subspaces of Clusters in SOF-Algorithm . . --- p.74 / Chapter 6.5.1 --- Technical Details in Phase I --- p.76 / Chapter 6.6 --- Technical Details in Phase II and Phase III --- p.88 / Chapter 6.6.1 --- Identify Outliers --- p.88 / Chapter 6.6.2 --- Subspace Quantization --- p.90 / Chapter 6.6.3 --- X-Tree Index Structure --- p.91 / Chapter 6.6.4 --- Compute GSOF and SOF --- p.95 / Chapter 6.6.5 --- Assign SO Values --- p.95 / Chapter 6.6.6 --- Multi-threads Programming --- p.96 / Chapter 6.7 --- Time Complexity --- p.97 / Chapter 6.8 --- Strength of SOF-Algorithm --- p.99 / Chapter 7 --- "Experiments on LOF' ，LOF"" and GridLOF" --- p.102 / Chapter 7.1 --- Datasets Used --- p.103 / Chapter 7.2 --- LOF' --- p.103 / Chapter 7.3 --- "LOF"" " --- p.109 / Chapter 7.4 --- GridLOF --- p.114 / Chapter 8 --- Empirical Results of SOF --- p.121 / Chapter 8.1 --- Synthetic Data Generation --- p.121 / Chapter 8.2 --- Experimental Setup --- p.124 / Chapter 8.3 --- Performance Measure --- p.124 / Chapter 8.3.1 --- Quality Measurement --- p.127 / Chapter 8.3.2 --- Scalability of SOF-Algorithm --- p.136 / Chapter 8.3.3 --- Effect of Parameters on SOF-Algorithm --- p.139 / Chapter 9 --- Conclusion --- p.140 / Bibliography --- p.142 / Publication --- p.149
| Identifer | oai:union.ndltd.org:cuhk.edu.hk/oai:cuhk-dr:cuhk_324318 |
| Date | January 2003 |
| Contributors | Chiu, Lai Mei., Chinese University of Hong Kong Graduate School. Division of Computer Science and Engineering. |
| Source Sets | The Chinese University of Hong Kong |
| Language | English, Chinese |
| Detected Language | English |
| Type | Text, bibliography |
| Format | print, xiii, 149 leaves : ill. ; 30 cm. |
| Rights | Use of this resource is governed by the terms and conditions of the Creative Commons “Attribution-NonCommercial-NoDerivatives 4.0 International” License (http://creativecommons.org/licenses/by-nc-nd/4.0/) |
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