A novel 2D-graph clustering method based on trust and similarity measures to enhance accuracy and coverage in recommender systems

DOI10.1016/J.INS.2017.12.007zbMath1461.68227OpenAlexW2772691914MaRDI QIDQ781906

Leily Sheugh, S. H. Alizadeh

Publication date: 20 July 2020

Published in: Information Sciences (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.ins.2017.12.007

zbMATH Keywords

accuracycoveragerecommender systemscold start2D-graph clustering

Mathematics Subject Classification ID

Classification and discrimination; cluster analysis (statistical aspects) (62H30) Theory of languages and software systems (knowledge-based systems, expert systems, etc.) for artificial intelligence (68T35)

Related Items (1)

Almost aggregations in the gravitational clustering to perform anomaly detection

Uses Software

• PRMLT

Cites Work

• Discovery Science
• Unnamed Item

This page was built for publication: A novel 2D-graph clustering method based on trust and similarity measures to enhance accuracy and coverage in recommender systems