# sars_tutorial

**Repository Path**: zjb_1994/sars_tutorial

## Basic Information

- **Project Name**: sars_tutorial
- **Description**: No description available
- **Primary Language**: Unknown
- **License**: MIT
- **Default Branch**: master
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 0
- **Created**: 2019-10-19
- **Last Updated**: 2020-12-19

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README


# Tutorial on Sequence-Aware Recommender Systems

This repository contains the material used in the hands-on session of the tutorials on Sequence-Aware Recommenders we gave
at [TheWebConf 2019](https://www2019.thewebconf.org/tutorials) and [ACM RecSys 2018](https://recsys.acm.org/recsys18/tutorials/#content-tab-1-4-tab).

## ACM CSUR Paper and TheWebConf 2019 Slides

### ACM Computing Surveys (CSUR) Paper
<img src="http://dl.acm.org/images/oa.gif" width="25" height="25" border="0" alt="ACM DL Author-ize service" style="vertical-align:middle"/><a href="https://dl.acm.org/authorize?N671306" title="Sequence-Aware Recommender Systems">Sequence-Aware Recommender Systems</a>  
<a href="http://dl.acm.org/author_page.cfm?id=83358752257" >Massimo Quadrana</a>, <a href="http://dl.acm.org/author_page.cfm?id=81548025673" >Paolo Cremonesi</a>, <a href="http://dl.acm.org/author_page.cfm?id=81100081930" >Dietmar Jannach</a>  
ACM Computing Surveys (CSUR), 2018

### TheWebConf 2019 Slides
1. [Introduction](slides/TheWebConf2019_01_Introduction.pdf)
2. [Algorithms](slides/TheWebConf2019_02_Algorithms.pdf)
3. [Evaluation](slides/TheWebConf2019_03_Evaluation.pdf)

## Running the code

You have two options to run the code contained in this repository:
1. Setup a new environment on your local machine and run the code locally (_highly recommended_).
2. Launch a new Binder instance by clicking on this badge [![Binder](https://mybinder.org/badge.svg)](https://mybinder.org/v2/gh/mquad/sars_tutorial/master). 

While we all know that setting up a new local environment is a slightly tedious process, Binder instances have strict resource limits (1-2GB of memory, max 100 concurrent users per repository). 
Also beware that Binder sessions automatically expire after 10 minutes of inactivity!  
So we *highly recommend* to set up a new local environment in advance by following the [Setup instructions](#setup-instructions).

### Setup instructions

1. First of all, clone this project to your local machine:
    ```bash
    git clone https://github.com/mquad/sars_tutorial.git
    ```

2. Now you need to set up a new python3 environment. We will use Anaconda/Miniconda for doing so.
If you don't have Anaconda/Minicoda already installed on your machine, click here to download [Miniconda](https://conda.io/miniconda.html) or [Anaconda](https://www.anaconda.com/download/) (**Python 3 version**).

3. After that, install the environment for this hands-on by running:
    ```bash
    cd sars_tutorial/
    conda env create --file environment.yml
    ```

4. (_Miniconda users only_) If you choose to install Miniconda before, you will now have to install Jupyter Notebook on your machine, just by running `conda install jupyter`. 
You can do it in your main python environment (necessarily in the `srs` env),  as long as you setup the kernel as explained after.
Anaconda users should already have Jupyter Notebook installed, so they can skip this step.

5. Then activate the environment with `source activate srs` or `conda activate srs`, and install a new `iptyhon` kernel by running:
    ```bash
    python -m ipykernel install --name srs
    ``` 
    If you get "Permission denied" error with the above command, try with
    ```bash
    python -m ipykernel install --name srs --user
    ``` 

6. Finally, launch the Jupyter Notebook with
    ```bash
    jupyter notebook --port=8888
    ```
and open it your browser at the address `localhost:8888`. 
(Beware, if port `8888` is already taken by another service, Jupyter Notebook will automatically open on a different one. Check out the startup log!).


### Running the notebooks

The notebooks used in this hands-on are listed in the main directory of this project, as shown below:

<img src="images/running_notebooks_1.png" width="300" >

Click on the name of the notebook to open it in a new window. The name of each running notebook is highlighted in green 
(in the screen above, the notebook `00_TopPopular` is the only one running).

Before starting to execute the notebook cells, you have to ensure that the kernel is properly set to `srs`, like in the screen below:

![](images/running_notebooks_2.png)

If it's not your case, change the kernel to `srs` by clicking on `Kernel > Change kernel > srs` in the menu bar, as shown below:

![](images/running_notebooks_3.png)

NOTE: this requires the installation of the `srs` kernel, as explained in the [Setup instructions](#setup-instructions).

You can now start running the cells in the notebook! Yay!


# Acknowledgments

We want to sincerely thank [Umberto Di Fabrizio](https://www.linkedin.com/in/umbertodifabrizio) for the help in the development of this repository back when he was a MSc student at Politecnico di Milano. Great job Umberto!