like2vec

Like2Vec is a neaborhood based recommendation algorithm that uses network embeddings to create latent representations of transactional history

The components of the pipeline are:

• Utility Matrix - LLR
• Network Embeddings
• Prediction
• Evaluation

Folder Structure

├── LICENSE
├── README.md          <- The top-level README for developers using this project.
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├── docs               <- A default Sphinx project; see sphinx-doc.org for details
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├── notebooks          <- Jupyter notebooks. Naming convention is a number (for ordering),
│                         the creator's initials, and a short `-` delimited description, e.g.
│                         `1.0-jja-initial-data-exploration`.
│
├── references         <- Data dictionaries, manuals, and all other explanatory materials.
│
├── reports            <- Generated analysis as HTML, PDF, LaTeX, etc.
│   └── figures        <- Generated graphics and figures to be used in reporting
│
├── src                <- Source code for project.
│   ├── embeddings     <- Module to create network embeddings.
│   │
│   ├── llr            <- Module to calculate log-likelihood ratio of transactions
│   │
│   ├── prediction     <- Module to create neighborhood-based predictions
│   │   
│   ├── evaluation     <- Module to evaluate predictions
│