Comparison of Selected Swarm Intelligence Algorithms in Student Courses Recommendation Application
Janusz F. Sobecki · International Journal of Software Engineering and Knowledge Engineering · 2014
In this paper a comparison of a few swarm intelligence algorithms applied in recommendation of student courses is presented. Swarm intelligence algorithms are nowadays successfully used in many areas, especially in optimization problems. To apply each swarm intelligence algorithm in recommender systems a special representation of the problem space is necessary. Here we present the comparison of efficiency of grade prediction of several evolutionary algorithms, such as: Ant Colony Optimization (ACO), Particle Swarm Optimization (PSO), Intelligent Weed Optimization (IWO), Bee Colony Optimization (BCO) and Bat Algorithm (BA).