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Information extraction and data mining from Chinese financial news.

Ng Anny. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2002. / Includes bibliographical references (leaves 139-142). / Abstracts in English and Chinese. / Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- Problem Definition --- p.2 / Chapter 1.2 --- Thesis Organization --- p.3 / Chapter 2 --- Chinese Text Summarization Using Genetic Algorithm --- p.4 / Chapter 2.1 --- Introduction --- p.4 / Chapter 2.2 --- Related Work --- p.6 / Chapter 2.3 --- Genetic Algorithm Approach --- p.10 / Chapter 2.3.1 --- Fitness Function --- p.11 / Chapter 2.3.2 --- Genetic operators --- p.14 / Chapter 2.4 --- Implementation Details --- p.15 / Chapter 2.5 --- Experimental results --- p.19 / Chapter 2.6 --- Limitations and Future Work --- p.24 / Chapter 2.7 --- Conclusion --- p.26 / Chapter 3 --- Event Extraction from Chinese Financial News --- p.27 / Chapter 3.1 --- Introduction --- p.28 / Chapter 3.2 --- Method --- p.29 / Chapter 3.2.1 --- Data Set Preparation --- p.29 / Chapter 3.2.2 --- Positive Word --- p.30 / Chapter 3.2.3 --- Negative Word --- p.31 / Chapter 3.2.4 --- Window --- p.31 / Chapter 3.2.5 --- Event Extraction --- p.32 / Chapter 3.3 --- System Overview --- p.33 / Chapter 3.4 --- Implementation --- p.33 / Chapter 3.4.1 --- Event Type and Positive Word --- p.34 / Chapter 3.4.2 --- Company Name --- p.34 / Chapter 3.4.3 --- Negative Word --- p.36 / Chapter 3.4.4 --- Event Extraction --- p.37 / Chapter 3.5 --- Stock Database --- p.38 / Chapter 3.5.1 --- Stock Movements --- p.39 / Chapter 3.5.2 --- Implementation --- p.39 / Chapter 3.5.3 --- Stock Database Transformation --- p.39 / Chapter 3.6 --- Performance Evaluation --- p.40 / Chapter 3.6.1 --- Performance measures --- p.40 / Chapter 3.6.2 --- Evaluation --- p.41 / Chapter 3.7 --- Conclusion --- p.45 / Chapter 4 --- Mining Frequent Episodes --- p.46 / Chapter 4.1 --- Introduction --- p.46 / Chapter 4.1.1 --- Definitions --- p.48 / Chapter 4.2 --- Related Work --- p.50 / Chapter 4.3 --- Double-Part Event Tree for the database --- p.56 / Chapter 4.3.1 --- Complexity of tree construction --- p.62 / Chapter 4.4 --- Mining Frequent Episodes with the DE-tree --- p.63 / Chapter 4.4.1 --- Conditional Event Trees --- p.66 / Chapter 4.4.2 --- Single Path Conditional Event Tree --- p.67 / Chapter 4.4.3 --- Complexity of Mining Frequent Episodes with DE-Tree --- p.67 / Chapter 4.4.4 --- An Example --- p.68 / Chapter 4.4.5 --- Completeness of finding frequent episodes --- p.71 / Chapter 4.5 --- Implementation of DE-Tree --- p.71 / Chapter 4.6 --- Method 2: Node-List Event Tree --- p.76 / Chapter 4.6.1 --- Tree construction --- p.79 / Chapter 4.6.2 --- Order of Position Bits --- p.83 / Chapter 4.7 --- Implementation of NE-tree construction --- p.84 / Chapter 4.7.1 --- Complexity of NE-Tree Construction --- p.86 / Chapter 4.8 --- Mining Frequent Episodes with NE-tree --- p.87 / Chapter 4.8.1 --- Conditional NE-Tree --- p.87 / Chapter 4.8.2 --- Single Path Conditional NE-Tree --- p.88 / Chapter 4.8.3 --- Complexity of Mining Frequent Episodes with NE-Tree --- p.89 / Chapter 4.8.4 --- An Example --- p.89 / Chapter 4.9 --- Performance evaluation --- p.91 / Chapter 4.9.1 --- Synthetic data --- p.91 / Chapter 4.9.2 --- Real data --- p.99 / Chapter 4.10 --- Conclusion --- p.103 / Chapter 5 --- Mining N-most Interesting Episodes --- p.104 / Chapter 5.1 --- Introduction --- p.105 / Chapter 5.2 --- Method --- p.106 / Chapter 5.2.1 --- Threshold Improvement --- p.108 / Chapter 5.2.2 --- Pseudocode --- p.112 / Chapter 5.3 --- Experimental Results --- p.112 / Chapter 5.3.1 --- Synthetic Data --- p.113 / Chapter 5.3.2 --- Real Data --- p.119 / Chapter 5.4 --- Conclusion --- p.121 / Chapter 6 --- Mining Frequent Episodes with Event Constraints --- p.122 / Chapter 6.1 --- Introduction --- p.122 / Chapter 6.2 --- Method --- p.123 / Chapter 6.3 --- Experimental Results --- p.125 / Chapter 6.3.1 --- Synthetic Data --- p.126 / Chapter 6.3.2 --- Real Data --- p.129 / Chapter 6.4 --- Conclusion --- p.131 / Chapter 7 --- Conclusion --- p.133 / Chapter A --- Test Cases --- p.135 / Chapter A.1 --- Text 1 --- p.135 / Chapter A.2 --- Text 2 --- p.137 / Bibliography --- p.139

Identiferoai:union.ndltd.org:cuhk.edu.hk/oai:cuhk-dr:cuhk_324005
Date January 2002
ContributorsNg, Anny., Chinese University of Hong Kong Graduate School. Division of Computer Science and Engineering.
Source SetsThe Chinese University of Hong Kong
LanguageEnglish, Chinese
Detected LanguageEnglish
TypeText, bibliography
Formatprint, xiv, 142 leaves : ill. ; 30 cm.
RightsUse 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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