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Graph-based recommendation with label propagation. / 基於圖傳播的推薦系統 / Ji yu tu chuan bo de tui jian xi tong

Wang, Dingyan. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2011. / Includes bibliographical references (p. 97-110). / Abstracts in English and Chinese. / Abstract --- p.ii / Acknowledgement --- p.vi / Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- Overview --- p.1 / Chapter 1.2 --- Motivations --- p.6 / Chapter 1.3 --- Contributions --- p.9 / Chapter 1.4 --- Organizations of This Thesis --- p.11 / Chapter 2 --- Background --- p.14 / Chapter 2.1 --- Label Propagation Learning Framework --- p.14 / Chapter 2.1.1 --- Graph-based Semi-supervised Learning --- p.14 / Chapter 2.1.2 --- Green's Function Learning Framework --- p.16 / Chapter 2.2 --- Recommendation Methods --- p.19 / Chapter 2.2.1 --- Traditional Memory-based Methods --- p.19 / Chapter 2.2.2 --- Traditional Model-based Methods --- p.20 / Chapter 2.2.3 --- Label Propagation Recommendation Models --- p.22 / Chapter 2.2.4 --- Latent Feature Recommendation Models . --- p.24 / Chapter 2.2.5 --- Social Recommendation Models --- p.25 / Chapter 2.2.6 --- Tag-based Recommendation Models --- p.25 / Chapter 3 --- Recommendation with Latent Features --- p.28 / Chapter 3.1 --- Motivation and Contributions --- p.28 / Chapter 3.2 --- Item Graph --- p.30 / Chapter 3.2.1 --- Item Graph Definition --- p.30 / Chapter 3.2.2 --- Item Graph Construction --- p.31 / Chapter 3.3 --- Label Propagation Recommendation Model with Latent Features --- p.33 / Chapter 3.3.1 --- Latent Feature Analysis --- p.33 / Chapter 3.3.2 --- Probabilistic Matrix Factorization --- p.35 / Chapter 3.3.3 --- Similarity Consistency Between Global and Local Views (SCGL) --- p.39 / Chapter 3.3.4 --- Item-based Green's Function Recommendation Based on SCGL --- p.41 / Chapter 3.4 --- Experiments --- p.41 / Chapter 3.4.1 --- Dataset --- p.43 / Chapter 3.4.2 --- Baseline Methods --- p.43 / Chapter 3.4.3 --- Metrics --- p.45 / Chapter 3.4.4 --- Experimental Procedure --- p.45 / Chapter 3.4.5 --- Impact of Weight Parameter u --- p.46 / Chapter 3.4.6 --- Performance Comparison --- p.48 / Chapter 3.5 --- Summary --- p.50 / Chapter 4 --- Recommendation with Social Network --- p.51 / Chapter 4.1 --- Limitation and Contributions --- p.51 / Chapter 4.2 --- A Social Recommendation Framework --- p.55 / Chapter 4.2.1 --- Social Network --- p.55 / Chapter 4.2.2 --- User Graph --- p.57 / Chapter 4.2.3 --- Social-User Graph --- p.59 / Chapter 4.3 --- Experimental Analysis --- p.60 / Chapter 4.3.1 --- Dataset --- p.61 / Chapter 4.3.2 --- Metrics --- p.63 / Chapter 4.3.3 --- Experiment Setting --- p.64 / Chapter 4.3.4 --- Impact of Control Parameter u --- p.65 / Chapter 4.3.5 --- Performance Comparison --- p.67 / Chapter 4.4 --- Summary --- p.69 / Chapter 5 --- Recommendation with Tags --- p.71 / Chapter 5.1 --- Limitation and Contributions --- p.71 / Chapter 5.2 --- Tag-Based User Modeling --- p.75 / Chapter 5.2.1 --- Tag Preference --- p.75 / Chapter 5.2.2 --- Tag Relevance --- p.78 / Chapter 5.2.3 --- User Interest Similarity --- p.80 / Chapter 5.3 --- Tag-Based Label Propagation Recommendation --- p.83 / Chapter 5.4 --- Experimental Analysis --- p.84 / Chapter 5.4.1 --- Douban Dataset --- p.85 / Chapter 5.4.2 --- Experiment Setting --- p.86 / Chapter 5.4.3 --- Metrics --- p.87 / Chapter 5.4.4 --- Impact of Tag and Rating --- p.88 / Chapter 5.4.5 --- Performance Comparison --- p.90 / Chapter 5.5 --- Summary --- p.92 / Chapter 6 --- Conclusions and Future Work --- p.94 / Chapter 6.0.1 --- Conclusions --- p.94 / Chapter 6.0.2 --- Future Work --- p.96 / Bibliography --- p.97

Identiferoai:union.ndltd.org:cuhk.edu.hk/oai:cuhk-dr:cuhk_327551
Date January 2011
ContributorsWang, Dingyan., 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, xiii, 110 p. : 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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