by Ng, King Kwok. / Thesis submitted in: December 1999. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2000. / Includes bibliographical references (leaves 99-104). / Abstracts in English and Chinese. / Acknowledgments --- p.ii / Abstract --- p.iii / Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- Data Mining and Rule Discovery --- p.1 / Chapter 1.1.1 --- Association Rule --- p.3 / Chapter 1.1.2 --- Sequential Pattern --- p.4 / Chapter 1.1.3 --- Dependence Rule --- p.6 / Chapter 1.2 --- Association Rule Mining --- p.8 / Chapter 1.3 --- Contributions --- p.9 / Chapter 1.4 --- Outline of the Thesis --- p.10 / Chapter 2 --- Related Work on Association Rule Mining --- p.11 / Chapter 2.1 --- Batch Algorithms --- p.11 / Chapter 2.1.1 --- The Apriori Algorithm --- p.11 / Chapter 2.1.2 --- The DIC Algorithm --- p.13 / Chapter 2.1.3 --- The Partition Algorithm --- p.15 / Chapter 2.1.4 --- The Sampling Algorithm --- p.15 / Chapter 2.2 --- Incremental Association Rule Mining --- p.16 / Chapter 2.2.1 --- The FUP Algorithm --- p.17 / Chapter 2.2.2 --- The FUP2 Algorithm --- p.18 / Chapter 2.2.3 --- The FUP* Algorithm --- p.19 / Chapter 2.2.4 --- The Negative Border Method --- p.20 / Chapter 2.2.5 --- Limitations of Existing Incremental Association Rule Mining Algorithms --- p.21 / Chapter 3 --- A New Incremental Association Rule Mining Approach --- p.23 / Chapter 3.1 --- Outline for the Proposed Approach --- p.23 / Chapter 3.2 --- Our New Approach --- p.26 / Chapter 3.2.1 --- The IDIC_M Algorithm --- p.26 / Chapter 3.2.2 --- A Variant Algorithm: The IDIC_S Algorithm --- p.29 / Chapter 3.3 --- Performance Evaluation of Our Approach --- p.30 / Chapter 3.3.1 --- Experimental Results for Algorithm IDIC_M --- p.30 / Chapter 3.3.2 --- Experimental Results for Algorithm IDIC_S --- p.35 / Chapter 3.4 --- Discussion --- p.39 / Chapter 4 --- Related Work on Multiple_Level AR and Belief-Driven Mining --- p.41 / Chapter 4.1 --- Background on Multiple_Level Association Rules --- p.41 / Chapter 4.2 --- Related Work on Multiple-Level Association Rules --- p.42 / Chapter 4.2.1 --- The Basic Algorithm --- p.42 / Chapter 4.2.2 --- The Cumulate Algorithm --- p.44 / Chapter 4.2.3 --- The EstMerge Algorithm --- p.44 / Chapter 4.2.4 --- Using Hierarchy-Information Encoded Transaction Table --- p.45 / Chapter 4.3 --- Background on Rule Mining in the Presence of User Belief --- p.46 / Chapter 4.4 --- Related Work on Rule Mining in the Presence of User Belief --- p.47 / Chapter 4.4.1 --- Post-Analysis of Learned Rules --- p.47 / Chapter 4.4.2 --- Using General Impressions to Analyze Discovered Classification Rules --- p.49 / Chapter 4.4.3 --- A Belief-Driven Method for Discovering Unexpected Patterns --- p.50 / Chapter 4.4.4 --- Constraint-Based Rule Mining --- p.51 / Chapter 4.5 --- Limitations of Existing Approaches --- p.52 / Chapter 5 --- Multiple-Level Association Rules Mining in the Presence of User Belief --- p.54 / Chapter 5.1 --- User Belief Under Taxonomy --- p.55 / Chapter 5.2 --- Formal Definition of Rule Interestingness --- p.57 / Chapter 5.3 --- The MARUB_E Mining Algorithm --- p.61 / Chapter 6 --- Experiments on MARUB_E --- p.64 / Chapter 6.1 --- Preliminary Experiments --- p.64 / Chapter 6.2 --- Experiments on Synthetic Data --- p.68 / Chapter 6.3 --- Experiments on Real Data --- p.71 / Chapter 7 --- Dealing with Vague Belief of User --- p.76 / Chapter 7.1 --- User Belief Under Taxonomy --- p.76 / Chapter 7.2 --- Relationship with Constraint-Based Rule Mining --- p.79 / Chapter 7.3 --- Formal Definition of Rule Interestingness --- p.79 / Chapter 7.4 --- The MARUB_V Mining Algorithm --- p.81 / Chapter 8 --- Experiments on MARUB_V --- p.84 / Chapter 8.1 --- Preliminary Experiments --- p.84 / Chapter 8.1.1 --- Experiments on Synthetic Data --- p.87 / Chapter 8.1.2 --- Experiments on Real Data --- p.93 / Chapter 9 --- Conclusions and Future Work --- p.96 / Chapter 9.1 --- Conclusions --- p.95 / Chapter 9.2 --- Future Work --- p.97
| Identifer | oai:union.ndltd.org:cuhk.edu.hk/oai:cuhk-dr:cuhk_323268 |
| Date | January 2000 |
| Contributors | Ng, King Kwok., Chinese University of Hong Kong Graduate School. Division of Systems Engineering and Engineering Management. |
| Source Sets | The Chinese University of Hong Kong |
| Language | English, Chinese |
| Detected Language | English |
| Type | Text, bibliography |
| Format | print, xiii, 104 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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