Commercial intention detection on Twitter.

• Other Authors: Zhu, Yi.
• Format: Others
• Language: English; Chinese
• Published: 2011
• Subjects: Internet marketing; Online social networks
• Online Access: http://library.cuhk.edu.hk/record=b5894620; http://repository.lib.cuhk.edu.hk/en/item/cuhk-327393

Zhu, Yi. === Thesis (M.Phil.)--Chinese University of Hong Kong, 2011. === Includes bibliographical references (p. 136-148). === Abstracts in English and Chinese. === Abstract --- p.i === Acknowledgement --- p.vi === Chapter 1 --- Introduction --- p.1 === Chapter 1.1 --- Overview --- p.1 === Chapter 1.2 --- Motivations of Detecting Commercial Intention --- p.4 === Chapter 1.3 --- Problem Definition for Commercial Intention Detection --- p.6 === Chapter 1.4 --- Contributions --- p.8 === Chapter 1.5 --- Thesis Organization --- p.9 === Chapter 2 --- Literature Review --- p.12 === Chapter 2.1 --- Twitter and Tweets Analysis --- p.13 === Chapter 2.2 --- Intention Detection --- p.17 === Chapter 2.2.1 --- User Intention Mining --- p.17 === Chapter 2.2.2 --- Commercial Intention Mining --- p.18 === Chapter 2.3 --- Similar Task: Opinion Mining --- p.18 === Chapter 2.4 --- NLP Techniques for Commercial Intention Detection --- p.20 === Chapter 2.4.1 --- Words Semantic Similarity --- p.21 === Chapter 2.4.2 --- Short Text Similarity --- p.25 === Chapter 2.5 --- Hierarchical Classification --- p.26 === Chapter 2.5.1 --- Hierarchical Classifiers Overview --- p.26 === Chapter 2.5.2 --- Construction of Hierarchy --- p.27 === Chapter 2.5.3 --- Taxonomy of Hierarchical Classification --- p.28 === Chapter 3 --- System Overview --- p.31 === Chapter 3.1 --- Feasibility of Commercial Intention Detection --- p.31 === Chapter 3.2 --- System Design and Architecture --- p.33 === Chapter 3.3 --- Components of READ-MIND --- p.35 === Chapter 3.3.1 --- Preprocessing --- p.35 === Chapter 3.3.2 --- Centroid Word Locator --- p.37 === Chapter 3.3.3 --- Commercial Intention Detector --- p.38 === Chapter 3.3.4 --- Tweet Classifier --- p.40 === Chapter 3.3.5 --- Advertisement Mapping --- p.41 === Chapter 3.4 --- System Work Flow --- p.42 === Chapter 3.4.1 --- System Dataflow and Controlflow --- p.42 === Chapter 3.4.2 --- User Interface --- p.42 === Chapter 3.5 --- System Speed Up --- p.43 === Chapter 3.6 --- Summary --- p.45 === Chapter 4 --- Natural Language Processing on Tweets --- p.46 === Chapter 4.1 --- NLP Techniques in READ-MIND --- p.46 === Chapter 4.2 --- Centroid Word Locator --- p.47 === Chapter 4.2.1 --- Centroid Word --- p.47 === Chapter 4.2.2 --- Locating Centroid Word --- p.48 === Chapter 4.2.3 --- Centroid Word Pair --- p.50 === Chapter 4.2.4 --- Locating Centroid Word Pair --- p.54 === Chapter 4.3 --- Semantic Relatedness Between Tweets --- p.59 === Chapter 4.3.1 --- Relatedness with a Words Set --- p.60 === Chapter 4.3.2 --- Relatedness between Tweets --- p.62 === Chapter 4.3.3 --- Words Similarity --- p.63 === Chapter 4.4 --- Summary --- p.65 === Chapter 5 --- Tweets Classification --- p.66 === Chapter 5.1 --- Two Stages of Tweets Classification --- p.66 === Chapter 5.2 --- Commercial Intention Detector --- p.68 === Chapter 5.2.1 --- Intuitive Method --- p.68 === Chapter 5.2.2 --- Binary Classification --- p.70 === Chapter 5.3 --- Tweet Categorization --- p.72 === Chapter 5.3.1 --- Build Hierarchical Classifier --- p.73 === Chapter 5.3.2 --- Hierarchical Classification --- p.81 === Chapter 5.4 --- Summary --- p.83 === Chapter 6 --- Empirical Study --- p.84 === Chapter 6.1 --- Objective of Empirical Study --- p.84 === Chapter 6.2 --- Experiment Setup and Evaluation Methodology --- p.85 === Chapter 6.2.1 --- Simulation Environment --- p.85 === Chapter 6.2.2 --- Tweets Data Set --- p.86 === Chapter 6.2.3 --- Labeling Process --- p.87 === Chapter 6.2.4 --- Evaluation Methodology --- p.88 === Chapter 6.3 --- Compare Algorithms in Components --- p.90 === Chapter 6.3.1 --- Centroid Word VS. Centroid Word Pair --- p.91 === Chapter 6.3.2 --- Semantic Similarity Comparison --- p.92 === Chapter 6.3.3 --- Methods in Commercial Intention Detector --- p.93 === Chapter 6.3.4 --- Structure of Hierarchy --- p.94 === Chapter 6.3.5 --- Training Source of Tweets Classifier --- p.95 === Chapter 6.3.6 --- Summary --- p.96 === Chapter 6.4 --- Parameter Settings Comparison --- p.97 === Chapter 6.4.1 --- Impact of Varying Parameters --- p.97 === Chapter 6.4.2 --- Discussion on Parameter Setting --- p.98 === Chapter 6.5 --- Comparison of READ-MIND and Baseline Method --- p.100 === Chapter 6.6 --- Time Cost Analysis --- p.101 === Chapter 6.6.1 --- Time Cost to Process Tweets --- p.101 === Chapter 6.6.2 --- Comparison with Baseline --- p.102 === Chapter 6.6.3 --- Analysis on Real-Time Property --- p.103 === Chapter 6.7 --- TCI Categories Comparison --- p.106 === Chapter 6.7.1 --- Results for Different TCIs --- p.106 === Chapter 6.7.2 --- Comparison of Different TCIs --- p.107 === Chapter 6.8 --- Summary --- p.108 === Chapter 7 --- Conclusion --- p.109 === Chapter 7.1 --- Conclusion --- p.109 === Chapter 7.2 --- Future Work --- p.111 === Chapter A --- List of Abbreviations --- p.112 === Chapter B --- List of Symbols --- p.114 === Chapter C --- Proof --- p.117 === Chapter D --- System Work Flow --- p.120 === Chapter E --- Algorithms --- p.123 === Chapter F --- Detailed Experimental Results --- p.129 === Bibliography --- p.136