Elliot: a Comprehensive and Rigorous Framework for Reproducible Recommender Systems Evaluation

TL;DR

Elliot is a comprehensive framework designed to streamline and reproduce the entire process of evaluating recommender systems, addressing the complexity and variability in current experimental setups.

Contribution

It introduces an exhaustive, configurable framework that automates data processing, hyperparameter optimization, model comparison, and statistical analysis for recommender systems evaluation.

Findings

Supports 13 data splitting strategies and 8 filtering approaches.

Optimizes hyperparameters for 50 recommendation algorithms using 51 strategies.

Provides extensive metrics and statistical tests for thorough evaluation.

Abstract

Recommender Systems have shown to be an effective way to alleviate the over-choice problem and provide accurate and tailored recommendations. However, the impressive number of proposed recommendation algorithms, splitting strategies, evaluation protocols, metrics, and tasks, has made rigorous experimental evaluation particularly challenging. Puzzled and frustrated by the continuous recreation of appropriate evaluation benchmarks, experimental pipelines, hyperparameter optimization, and evaluation procedures, we have developed an exhaustive framework to address such needs. Elliot is a comprehensive recommendation framework that aims to run and reproduce an entire experimental pipeline by processing a simple configuration file. The framework loads, filters, and splits the data considering a vast set of strategies (13 splitting methods and 8 filtering approaches, from temporal training-test splitting to nested K-folds Cross-Validation). Elliot optimizes hyperparameters (51 strategies) for several recommendation algorithms (50), selects the best models, compares them with the baselines providing intra-model statistics, computes metrics (36) spanning from accuracy to beyond-accuracy, bias, and fairness, and conducts statistical analysis (Wilcoxon and Paired t-test). The aim is to provide the researchers with a tool to ease (and make them reproducible) all the experimental evaluation phases, from data reading to results collection. Elliot is available on GitHub (https://github.com/sisinflab/elliot).