Cornac

New models

- Hidden Factors and Hidden Topics (HFT) (196)

New features and improvements

- Amazon Clothing dataset (197)
- CountVectorizer updated with vocab conditions (193)

New features and improvements

- Rename `Module` to `Modality`
- Add a tutorial for adding a new model into Cornac
- Reorder the list of models by year then alphabetically
- Update description, tagline
- Improve documentation

New models

- Variational Autoencoder for Collaborative Filtering (VAECF)
- Collaborative Topic Modelling (CTR)

New features and improvements

- Update `CVAE` to use mini-batch gradient descent
- Remove `stopwords` from `TextModule` and `CountVectorizer`, only input `stopwords` directly to `BaseTokenizer`
- `GraphModule` can build `KNN` from input feature matrix
- Fix bug of partitioning in `CrossValidation`
- Swap both `ids` according to data in `FeatureModule` and `TextModule`

New models

- Collaborative Variational Autoencoder (CVAE)

New features and improvements

- Update `from_splits()` function of `BaseMethod` to support multimodal data modules
- Data modules `build()` functions return `self`

New models

- Convolutional Matrix Factorization (ConvMF)
- Collaborative Deep Ranking (CDR)
- Visual Matrix Factorization (VMF)
- Matrix Co-Factorization (MCF)
- Social Bayesian Personalized Ranking (SBPR)
- Social Recommendation (SoRec)


New built-in datasets

- Netflix
- Tradesy
- Amazon Office
- CiteULike
- Epinions

New features and improvements

- Support multimodal recommenders with new data module including `TextModule`, `ImageModule`, and `GraphModule` in `data`.
- `Reader` support data filtering based on `set of users/items` and `user/item threshold`.
- Models can access to `user_text`, `user_image`, `user_graph`, `item_text`, `item_image`, and `item_graph` through `MultimodalTrainSet` which is input of the `fit()` function.

Credits

Thanks to our 4 contributors (alphabetical) whose commits are featured in this release:

binhtrantt jyguo saghiles tqtg

New models

- Bayesian Personalized Ranking (BPR)
- Collaborative Context Poisson Factorization (C2PF)
- Collaborative Deep Learning (CDL)
- Collaborative Ordinal Embedding (COE)
- Hierarchical Poisson Factorization (HPF)
- Indexable Bayesian Personalized Ranking (IBPR)
- Online Indexable Bayesian Personalized Ranking (Online IBPR)
- Probabilistic Collaborative Representation Learning (PCRL)
- Probabilistic Matrix Factorization (PMF)
- Spherical K-means (SKM)
- Visual Bayesian Personalized Ranking (VBPR)

Credits

Thanks to our 5 contributors (alphabetical) whose commits are featured in this release:

Andrew-DungLe jyguo llkute saghiles tqtg