DeepFM model based Trustworthy Web Service Recommendation System
Hema Priya N, N. Gopikarani, Shymala Gowri S, R. Ruthravarshini · 2025
In today's changing web environment, users find it difficult to choose reliable services because of the variety and unpredictability of online platforms. This paper presents a Trustworthy Web Service Recommendation System that uses a DeepFM model along with a self-attention mechanism to offer accurate, privacy-friendly, and personalized service recommendations. By examining user behaviour, service features, and previous interactions, the system generates high-quality recommendations. Furthermore, a privacy-preserving module protects data, and a trust score mechanism increases confidence in the chosen services.