Lai Kwok-yin. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2001. / Includes bibliographical references (leaves 125-130). / Abstracts in English and Chinese. / Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- Automatic Textual Document Categorization --- p.1 / Chapter 1.2 --- Meta-Learning Approach For Text Categorization --- p.3 / Chapter 1.3 --- Contributions --- p.6 / Chapter 1.4 --- Organization of the Thesis --- p.7 / Chapter 2 --- Related Work --- p.9 / Chapter 2.1 --- Existing Automatic Document Categorization Approaches --- p.9 / Chapter 2.2 --- Existing Meta-Learning Approaches For Information Retrieval --- p.14 / Chapter 2.3 --- Our Meta-Learning Approaches --- p.20 / Chapter 3 --- Document Pre-Processing --- p.22 / Chapter 3.1 --- Document Representation --- p.22 / Chapter 3.2 --- Classification Scheme Learning Strategy --- p.25 / Chapter 4 --- Linear Combination Approach --- p.30 / Chapter 4.1 --- Overview --- p.30 / Chapter 4.2 --- Linear Combination Approach - The Algorithm --- p.33 / Chapter 4.2.1 --- Equal Weighting Strategy --- p.34 / Chapter 4.2.2 --- Weighting Strategy Based On Utility Measure --- p.34 / Chapter 4.2.3 --- Weighting Strategy Based On Document Rank --- p.35 / Chapter 4.3 --- Comparisons of Linear Combination Approach and Existing Meta-Learning Methods --- p.36 / Chapter 4.3.1 --- LC versus Simple Majority Voting --- p.36 / Chapter 4.3.2 --- LC versus BORG --- p.38 / Chapter 4.3.3 --- LC versus Restricted Linear Combination Method --- p.38 / Chapter 5 --- The New Meta-Learning Model - MUDOF --- p.40 / Chapter 5.1 --- Overview --- p.41 / Chapter 5.2 --- Document Feature Characteristics --- p.42 / Chapter 5.3 --- Classification Errors --- p.44 / Chapter 5.4 --- Linear Regression Model --- p.45 / Chapter 5.5 --- The MUDOF Algorithm --- p.47 / Chapter 6 --- Incorporating MUDOF into Linear Combination approach --- p.52 / Chapter 6.1 --- Background --- p.52 / Chapter 6.2 --- Overview of MUDOF2 --- p.54 / Chapter 6.3 --- Major Components of the MUDOF2 --- p.57 / Chapter 6.4 --- The MUDOF2 Algorithm --- p.59 / Chapter 7 --- Experimental Setup --- p.66 / Chapter 7.1 --- Document Collection --- p.66 / Chapter 7.2 --- Evaluation Metric --- p.68 / Chapter 7.3 --- Component Classification Algorithms --- p.71 / Chapter 7.4 --- Categorical Document Feature Characteristics for MUDOF and MUDOF2 --- p.72 / Chapter 8 --- Experimental Results and Analysis --- p.74 / Chapter 8.1 --- Performance of Linear Combination Approach --- p.74 / Chapter 8.2 --- Performance of the MUDOF Approach --- p.78 / Chapter 8.3 --- Performance of MUDOF2 Approach --- p.87 / Chapter 9 --- Conclusions and Future Work --- p.96 / Chapter 9.1 --- Conclusions --- p.96 / Chapter 9.2 --- Future Work --- p.98 / Chapter A --- Details of Experimental Results for Reuters-21578 corpus --- p.99 / Chapter B --- Details of Experimental Results for OHSUMED corpus --- p.114 / Bibliography --- p.125
| Identifer | oai:union.ndltd.org:cuhk.edu.hk/oai:cuhk-dr:cuhk_323542 |
| Date | January 2001 |
| Contributors | Lai, Kwok-yin., 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, xiv, 130 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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