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COMP 4332 Tutorial 10 April 12 Yin Zhu email@example.com CF tools 1
Models & Tools KNN Models Implement yourself Matrix Factorization Models Probabilistic MF [DEMO] Factorization machines [DEMO] 2
KNN Model Neighborhood similarity Normalization factor Base rating
Matrix Factorization 4
Predicting missing values as recommendation 5
Matrix Factorization Model X m n m n U VTVT k k User parameters Item parameters Base Ratings
PMF Demo Matlab code: http://www.mit.edu/~rsalakhu/BPMF.html Implement PMF & Bayesian PMF PMF is much faster than BPMF 7
Factorization Machine Demo libFM, its manual and paper libFMmanualpaper 8
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Multiplication Find the missing value x __ = 32.
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EigenRank: A ranking oriented approach to collaborative filtering By Nathan N. Liu and Qiang Yang Presented by Zachary 1.
The Summary of My Work In Graduate Grade One Reporter: Yuanshuai Sun
Recommender Systems Problem formulation Machine Learning.
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User Interests Imbalance Exploration in Social Recommendation: A Fitness Adaptation Authors : Tianchun Wang, Xiaoming Jin, Xuetao Ding, and Xiaojun Ye.
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Active Collaborative Filtering Machine Learning Group Department of Computer Science University of Toronto.
Worksheet Answers Matrix worksheet And Matrices Review.
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Item Based Collaborative Filtering Recommendation Algorithms Badrul Sarvar, George Karypis, Joseph Konstan & John Riedl.
2016/2/4Course Introduction1 COMP 4332, RMBI 4330 Advanced Data Mining (Spring 2012) Qiang Yang Hong Kong University of Science and Technology
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ICONIP 2010, Sydney, Australia 1 An Enhanced Semi-supervised Recommendation Model Based on Green’s Function Dingyan Wang and Irwin King Dept. of Computer.
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Regression “A new perspective on freedom” TexPoint fonts used in EMF. Read the TexPoint manual before you delete this box.: AAA A A A A AAA A A.
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Supervisor: Associate Prof. Jiuyong Li(John) Student: Kang Sun Date: 28 th May 2010.
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