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Automatic topic detection of multi-lingual news stories.

Wong Kam Lai. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2000. / Includes bibliographical references (leaves 92-98). / Abstracts in English and Chinese. / Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- Our Contributions --- p.5 / Chapter 1.2 --- Organization of this Thesis --- p.5 / Chapter 2 --- Literature Review --- p.7 / Chapter 2.1 --- Dragon Systems --- p.7 / Chapter 2.2 --- Carnegie Mellon University (CMU) --- p.9 / Chapter 2.3 --- University of Massachusetts (UMass) --- p.10 / Chapter 2.4 --- IBM T.J. Watson Research Center --- p.11 / Chapter 2.5 --- BBN Technologies --- p.12 / Chapter 2.6 --- National Taiwan University (NTU) --- p.13 / Chapter 2.7 --- Drawbacks of Existing Approaches --- p.14 / Chapter 3 --- Overview of Proposed Approach --- p.15 / Chapter 3.1 --- News Source --- p.15 / Chapter 3.2 --- Story Preprocessing --- p.18 / Chapter 3.3 --- Concept Term Generation --- p.20 / Chapter 3.4 --- Named Entity Extraction --- p.21 / Chapter 3.5 --- Gross Translation of Chinese to English --- p.21 / Chapter 3.6 --- Topic Detection method --- p.22 / Chapter 3.6.1 --- Deferral Period --- p.22 / Chapter 3.6.2 --- Detection Approach --- p.23 / Chapter 4 --- Concept Term Model --- p.25 / Chapter 4.1 --- Background of Contextual Analysis --- p.25 / Chapter 4.2 --- Concept Term Generation --- p.28 / Chapter 4.2.1 --- Concept Generation Algorithm --- p.28 / Chapter 4.2.2 --- Concept Term Representation for Detection --- p.33 / Chapter 5 --- Topic Detection Model --- p.35 / Chapter 5.1 --- Text Representation and Term Weights --- p.35 / Chapter 5.1.1 --- Story Representation --- p.35 / Chapter 5.1.2 --- Topic Representation --- p.43 / Chapter 5.1.3 --- Similarity Score --- p.43 / Chapter 5.1.4 --- Time adjustment scheme --- p.46 / Chapter 5.2 --- Gross Translation Method --- p.48 / Chapter 5.3 --- The Detection System --- p.50 / Chapter 5.3.1 --- Detection Requirement --- p.50 / Chapter 5.3.2 --- The Top Level Model --- p.52 / Chapter 5.4 --- The Clustering Algorithm --- p.55 / Chapter 5.4.1 --- Similarity Calculation --- p.55 / Chapter 5.4.2 --- Grouping Related Elements --- p.56 / Chapter 5.4.3 --- Topic Identification --- p.60 / Chapter 6 --- Experimental Results and Analysis --- p.63 / Chapter 6.1 --- Evaluation Model --- p.63 / Chapter 6.1.1 --- Evaluation Methodology --- p.64 / Chapter 6.2 --- Experiments on the effects of tuning the parameter --- p.68 / Chapter 6.2.1 --- Experiment Setup --- p.68 / Chapter 6.2.2 --- Results and Analysis --- p.69 / Chapter 6.3 --- Experiments on the effects of named entities and concept terms --- p.74 / Chapter 6.3.1 --- Experiment Setup --- p.74 / Chapter 6.3.2 --- Results and Analysis --- p.75 / Chapter 6.4 --- Experiments on the effect of using time adjustment --- p.77 / Chapter 6.4.1 --- Experiment Setup --- p.77 / Chapter 6.4.2 --- Results and Analysis --- p.79 / Chapter 6.5 --- Experiments on mono-lingual detection --- p.80 / Chapter 6.5.1 --- Experiment Setup --- p.80 / Chapter 6.5.2 --- Results and Analysis --- p.80 / Chapter 7 --- Conclusions and Future Work --- p.83 / Chapter 7.1 --- Conclusions --- p.83 / Chapter 7.2 --- Future Work --- p.85 / Chapter A --- List of Topics annotated for TDT3 Corpus --- p.86 / Chapter B --- Matching evaluation topics to hypothesized topics --- p.90 / Bibliography --- p.92

Identiferoai:union.ndltd.org:cuhk.edu.hk/oai:cuhk-dr:cuhk_323212
Date January 2000
ContributorsWong, Kam Lai., Chinese University of Hong Kong Graduate School. Division of Systems Engineering and Engineering Management.
Source SetsThe Chinese University of Hong Kong
LanguageEnglish, Chinese
Detected LanguageEnglish
TypeText, bibliography
Formatprint, xiii, 98 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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