singhman / MovieRecommendationEngine
An user based and item based movie rating prediction recommender system based on data provided by MovieLens using memory-based Collaborative filtering technique by utilizing Pearson correlation, Euclidean distances, Cosine distances, and K-nearest neighbors algorithms
☆10Updated 9 years ago
Alternatives and similar repositories for MovieRecommendationEngine:
Users that are interested in MovieRecommendationEngine are comparing it to the libraries listed below
- This example uses the lightfm recommender system library to train a hybrid content-based + collaborative algorithm that uses the WARP los…☆9Updated 8 years ago
- Recommendation algorithms based on MovieLens☆11Updated 5 years ago
- 利用MovieLens数据，Pearson相似度，分别基于User和Item构建一个简单的kNN推荐系统，并给出RMSE评测☆68Updated 6 years ago
- Attention,Factorization Machine, Deep Learning, Recommender System☆39Updated 7 years ago
- SVD & BPR+MatrixFactorization using a movie rating dataset; RNN+BPR+BPTT using taobao marketing dataset☆51Updated 7 years ago
- Applied weight tying technique to RNN based recommendation model. Implemented with Tensorflow and Keras.☆53Updated 6 years ago
- Implemented Item, User and Hybrid based Collaborative Filtering☆158Updated 9 years ago
- Explore CNN/LSTM/GRU parallel architectures for movie recommendations using Keras & TensorFlow in Python☆51Updated 7 years ago
- uses collaborative and content based filtering techniques☆14Updated 8 years ago
- A Hybrid recommendation engine built on deep learning architecture, which has the potential to combine content-based and collaborative fi…☆32Updated 6 years ago
- This is a movie recommendation system with tensorflow. Dataset is MovieLens.☆20Updated 6 years ago
- Movie Recommendation System using the MovieLens dataset☆19Updated 7 years ago
- The hybrid model combining stacked denoising autoencoder with matrix factorization is applied, to predict the customer purchase behavior …☆70Updated 6 years ago
- building a recommendation system using graph search methodologies. We will be comparing these different approaches and closely observe t…☆64Updated 8 years ago
- Probabilistic Matrix Factorization with Social Trust for Recommendation (Ma et al. SIGIR 2009)☆19Updated 8 years ago
- ACM RecSys Challenge 2016: Job recommender system for XING☆8Updated 8 years ago
- A fork from https://github.com/hexiangnan/neural_collaborative_filtering. Change keras version to v2.1.3, and use tensorflow as the back…☆25Updated 7 years ago
- ☆19Updated 8 years ago
- TrustSVD: Collaborative Filtering with Both the Explicit and Implicit Influence of User Trust and of Item Ratings☆21Updated 6 years ago
- The purpose of our research is to study reinforcement learning approaches to building a movie recommender system. We formulate the proble…☆119Updated 5 years ago
- A Hybrid Recommendation system which uses Content embeddings and augments them with collaborative features. Weighted Combination of embed…☆17Updated 2 years ago
- code:Hidden factors and hidden topics: Understanding rating dimensions with review text.☆23Updated 8 years ago
- 蚂蚁金服-用户精确定位比赛☆12Updated 7 years ago
- Recommendation Models in TensorFlow☆46Updated 6 years ago
- This codes is used for computing the CTR in a recommendation system.☆17Updated 7 years ago
- Learning to Recommend using a Deep Reinforcement Agent☆23Updated 8 years ago
- CFRBM is a implementation of the RBM model to the collaborative filtering task☆40Updated 7 years ago
- Predict and recommend the news articles, user is most likely to click in real time.☆30Updated 7 years ago
- Recommendation System implementation which includes user based collaborative filtering, item based recommender and content boosted collab…☆19Updated 10 years ago
- recommendation system written by matlab codes☆47Updated 5 years ago