Work

RecKG-Web: A web-based interactive visualization tool for standardized knowledge graphs in recommender systems

Year: 2025

Type: software-paper

Abstract: Knowledge graphs (KG) enhance recommender systems (RS) by addressing challenges like the long-tail and cold-start problems through rich semantic relationships. However, inconsistent metadata across RS datasets limits interoperability. To solve this, we present RecKG-Web, a user-friendly application that standardizes and integrates heterogeneous datasets using the RecKG format. It supports data upload, mapping, graph-based visualization, and dataset export, enabling cross-domain recommendations and improving accessibility for researchers and practitioners. RecKG-Web bridges the gap between KG theory and practice, advancing KG-aware RS development.

Source: SoftwareX

DOI: 10.1016/j.softx.2025.102319

Authors: Junhyung Park, Minhye Jeon, Euijong Lee, Young-Duk Seo

Institutions: Inha University, Chungbuk National University

Language: English

Topic: Recommender Systems and Techniques

Subfield: Information Systems

Field: Computer Science

Domain: Physical Sciences

Open Access status: gold

Estimated APC paid: $1,200

Funders: Inha University, Ministry of Science and ICT, South Korea, Institute for Information and Communications Technology Promotion