Publication Date
8-24-2018
Resource Type
Software
Abstract
This archive contains the scripts to replicate the experiment for our paper ["Can we leverage rating patterns from traditional users to enhance recommendations for children?" published in ACM RecSys by - Ion Madrazo Azpiazu, Michael Green, Oghenemaro Anuyah, and Maria Soledad Pera.]
### Requirements - Java - An R, Jupyter, Python, and Tidyverse installation. - The [MovieLens 1M](https://grouplens.org/datasets/movielens/) dataset, extracted into Data/input (you should have directory Data/ml-1m) - The Dogo dataset (or any dataset containing ratings provided by children) extracted into Data/input
### Instructions - Steps to run: - Install required software and data files enlisted in requirements. These directories and files should be present upon doing so: -Data/input/ml-1m (e.g. data/ml-1m/ratings.dat) -Data/input/Dogo (e.g., any children ratings file) - Run Jupyter notebook: - Create_Experimental_Datasets/Data_creation_notebook.ipynb - Run LibReC Experiment: - Input_Analysis/ - Visualize user-rating activity: - Rating_Distribution_Dogo_ML1M.ipynb
### On October 9, 2018 the downloaded zip file was revised to remove some lines of code that were intended for internal analyses only.
DOI
https://doi.org/10.18122/cs_scripts/6/boisestate
Use Restrictions
CC-BY-NC
Disclaimer of Warranty
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Recommended Citation
Azpiazu, Ion Madrazo; Green, Michael; Anuyah, Oghenemaro; and Pera, Maria Soledad, "Scripts for Can We Leverage Rating Patterns from Traditional Users to Enhance Recommendations for Children?" (2018). Computer Science Faculty Scripts and Data. 6.
https://scholarworks.boisestate.edu/cs_scripts/6