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Blog content mining: topic identification and evolution extraction.

Ng, Kuan Kit. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2009. / Includes bibliographical references (leaves 92-100). / Abstract also in Chinese. / Abstract --- p.i / Acknowledgement --- p.iii / Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- Blog Overview --- p.2 / Chapter 1.2 --- Motivation --- p.4 / Chapter 1.2.1 --- Blog Mining --- p.5 / Chapter 1.2.2 --- Topic Detection and Tracking --- p.8 / Chapter 1.3 --- Objectives and Contributions --- p.9 / Chapter 1.4 --- Proposed Methodology --- p.11 / Chapter 2 --- Related Work --- p.13 / Chapter 2.1 --- Web Document Clustering --- p.13 / Chapter 2.2 --- Document Clustering with Temporal Information --- p.15 / Chapter 2.3 --- Blog Mining --- p.17 / Chapter 3 --- Feature Extraction and Selection --- p.20 / Chapter 3.1 --- Blog Extraction and Content Cleaning --- p.21 / Chapter 3.1.1 --- Blog Parsing and Structure Identification --- p.22 / Chapter 3.1.2 --- Stop-word Removal --- p.24 / Chapter 3.1.3 --- Word Stemming --- p.25 / Chapter 3.1.4 --- Heuristic Content Cleaning and Multiword Grouping --- p.25 / Chapter 3.2 --- Feature Selection --- p.26 / Chapter 3.2.1 --- Term Frequency Inverse Document Frequency --- p.27 / Chapter 3.2.2 --- Term Contribution --- p.29 / Chapter 4 --- Blog Topic Extraction --- p.31 / Chapter 4.1 --- Requirements of Document Clustering --- p.32 / Chapter 4.1.1 --- Vector Space Modeling --- p.32 / Chapter 4.1.2 --- Similarity Measurement --- p.33 / Chapter 4.2 --- Document Clustering --- p.34 / Chapter 4.2.1 --- Partitional Clustering --- p.36 / Chapter 4.2.2 --- Hierarchial Clustering --- p.37 / Chapter 4.2.3 --- Density-Based Clustering --- p.38 / Chapter 4.3 --- Proposed Concept Clustering --- p.40 / Chapter 4.3.1 --- Semantic Distance between Concepts --- p.43 / Chapter 4.3.2 --- Bounded Density-Based Clustering --- p.47 / Chapter 4.3.3 --- Document Assignment with Topic Clusters --- p.57 / Chapter 4.4 --- Discussion --- p.58 / Chapter 5 --- Blog Topic Evolution --- p.61 / Chapter 5.1 --- Topic Evolution Graph --- p.61 / Chapter 5.2 --- Topic Evolution --- p.64 / Chapter 6 --- Experimental Result --- p.69 / Chapter 6.1 --- Evaluation of Topic Cluster --- p.70 / Chapter 6.1.1 --- Evaluation Criteria --- p.70 / Chapter 6.1.2 --- Evaluation Result --- p.73 / Chapter 6.2 --- Evaluation of Topic Evolution --- p.79 / Chapter 6.2.1 --- Results of Topic Evolution Graph --- p.80 / Chapter 6.2.2 --- Evaluation Criteria --- p.82 / Chapter 6.2.3 --- Evaluation of Topic Evolution --- p.83 / Chapter 6.2.4 --- Case Study --- p.84 / Chapter 7 --- Conclusions and Future Work --- p.88 / Chapter 7.1 --- Conclusions --- p.88 / Chapter 7.2 --- Future Work --- p.90 / Bibliography --- p.92 / Chapter A --- Stop Word List --- p.101 / Chapter B --- Feature Selection Comparison --- p.104 / Chapter C --- Topic Evolution --- p.106 / Chapter D --- Topic Cluster --- p.108

Identiferoai:union.ndltd.org:cuhk.edu.hk/oai:cuhk-dr:cuhk_326726
Date January 2009
ContributorsNg, Kuan Kit., 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, xi, 111 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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