D&D4Rec

Scope

The common recommendation pipeline involves many stages, from data preprocessing and model's training to recommendation performance evaluation. Unlike other pipeline stages, dataset preprocessing has generally received less attention in the literature, leading to a lack of standardization, comparability, and reproducibility of recommendation systems. To this end, we present our tutorial on "Standard Practices for Data Processing and Multimodal Feature Extraction in Recommendation with DataRec and Ducho (D&D4Rec)". To begin with, the tutorial will shed light on established strategies for data preprocessing in recommendation, aiming to provide a formal and comprehensive taxonomy of standard practices. Such theoretical notions will be complemented with a hands-on session on DataRec, a recently proposed framework for the standardization of data preprocessing in recommendation. Then, the tutorial will tailor a specific but popular scenario in recommendation, namely, multimodal recommendation. After presenting common procedures to extract and process multimodal information enhancing the user-item recommendation data, the tutorial will feature a second hands-on session on Ducho, a popular framework for multimodal feature extraction in recommendation. More details about the tutorial will be continuously updated and made available at this webpage.