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yuanhuan177's Projects

movierecommendation-1 icon movierecommendation-1

本项目使用两种算法来实现一个电影推荐系统,一个是CNN,另一个是矩阵分解的协同过滤。

music-top-recommend icon music-top-recommend

利用用户画像数据、物品元数据、用户行为数据为特征构建推荐系统,使用CB和CF算法做推荐召回,使用 Redis数 据库做缓存处理,结合机器学习LR算法推荐排序,达到粗排、精排效果,实现推荐引擎搭建。

my-learning-notes icon my-learning-notes

整理机器学习,深度学习,自然语言处理,推荐系统相关的各种学习笔记

newsrecommendsystem icon newsrecommendsystem

个性化新闻推荐系统,A news recommendation system involving collaborative filtering,content-based recommendation and hot news recommendation, can be adapted easily to be put into use in other circumstances.

parselawdocuments icon parselawdocuments

对收集的法律文档进行一系列分析,包括根据规范自动切分、案件相似度计算、案件聚类、法律条文推荐等(试验目前基于婚姻类案件,可扩展至其它领域)。

product-recommendation-system icon product-recommendation-system

:sunrise: 基于用户的协同过滤算法实现的商品推荐系统 https://github.com/MrQuJL/product-recommendation-system

project_amazon_reviews_nlp_recommender_system icon project_amazon_reviews_nlp_recommender_system

Mining , pre-processing and embedding over 1 million Amazon Movie & T.V. reviews to build a multi class Naive Bayes model and later a CNN-LSTM model (that uses the Naive Bayes model as a baseline) to predict rating from text. Interpreting the original classifier using local surrogate models using the LIME library. Using LDA topic modeling to build a theme based recommender from the reviews and using a model based collaborative filtering system using SVD matrix factorization to build a second recommender system.

recommendation icon recommendation

实现了基于协同过滤(UserCF)的模型、基于隐语义(LFM)的模型、基于图(PersonalRank)的模型,并结合三种模型的结果给出最终结果的推荐算法

recommondation-system icon recommondation-system

一些传统推荐算法的实现,包括基于内容的推荐,协同过滤,矩阵分解

recsys2019_deeplearning_evaluation icon recsys2019_deeplearning_evaluation

This is the repository of our article published in RecSys 2019 "Are We Really Making Much Progress? A Worrying Analysis of Recent Neural Recommendation Approaches"

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