Optimizing Field-Aware Factorization Machine with Particle Swarm Optimization on Online Ads Click-through Rate Prediction
Michael Reynaldo Phangtriastu, Sani Muhamad Isa · 2018 3rd International Conference on Computer and Communication Systems (ICCCS) · 2018
Online advertising industry is grow larger along with the increasing numbers of internet users. To make ads industry to be more efficient, prediction model for ads' click-through rate is needed. In this research, Field-aware Factorization Machine (FFM) is going to be optimized using Particle Swarm Optimization (PSO) on FFM parameters to increase the accuracy of the FFM. In this research, FFM and PSO-FFM is compared with accuracy and execution time. Our experimental results show PSO can increase FFM performance.