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Recommender System
- 개요
- 사용 이유
- 문제 정의
- 평가 지표
- Offline Test
- Online Test
- Simple Aggregate
- Popularity
- Rating
- 연관분석 : Association Analysis / Association Rule Mining
- 컨텐츠 기반 필터링 : Content-based Filtering / Content-based Recommendation
- TF-IDF : Term Frequency - Inverse Document Frequency
- 협업 필터링 : Collaborative Filtering
- NBCF : Neighborhood-Based Collaborative Filtering - Memory-Based CF
- UBCF : User-Based Collaborative Filtering
- IBCF : Item-Based Collaborative Filtering
- Rating Prediction
- UBCF - Absolute/Relative Rating
- IBCF - Absolute/Relative Rating
- Top-N Recommendation
- MBCF : Model-Based Collaborative Filtering
- Non-Parametic : kNN, SVD
- MF : Matrix Factorization
- Implicit Feedback VS Explicit Feedback
- MF for Implicit Feedback - ALS : Alternating Least Square
- BPR : Baysian Personalized Ranking
- Embedding
- Word2Vec
- CBOW
- SG : Skip-Gram
- SGNS : Skip-Gram Negative Sampling
- Item2Vec
- Word2Vec
- ANN : Approximate Nearest Neighbor
- ANNOY : spotify에서 개발한 tree-based ANN
- HNSW : Hierarchical Navigable Small World Graphs
- IVF : Inverted File Index
- PQ : Product Quantization
- Context-Aware Recommendation
- CTR : Click-Through Rate Prediction
- FM : Factorization Machine
- FFM : Field-aware Factorization Machine
- GBM : Gradient Boosting Machine
- XGBoost
- LightGBM
- CatBoost
- Deep Learning based Recommendation
- Recommender with MLP
- NCF : Neural Collaborative Filtering
- Recommender with AutoEncoder
- AutoRec
- CDAE
- Recommender with GNN
- NGCF : Neural Graph Collaborative Filtering
- LightGCN
- Recommender with RNN
- GRU4Rec
- CTR Prediction with DL
- Wide & Deep
- DeepFM
- DIN : Deep interest Network
- BST : Behavior Sequence Transformer
- MAB : Multi-Armed Bandit
- Greedy Algorithm
- Epsilon-Greedy Algorithm
- UCB : Upper Confidence Bound
- Thompson Sampling
- LinUCB
- Recommender with MLP
- NBCF : Neighborhood-Based Collaborative Filtering - Memory-Based CF
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