Journal of Emerging Technologies and Business Management
Article Title
Abstract
In this paper; we present our intensive research developing a high-performance and scalable Recommender System that is based on the heuristic Bacterial Foraging Algorithm. Our researcher illustrate opportunities to significantbr improve the performance of Item Based Recommender Systems up to 600 percent. Key Words: Data mining, reeommender system, bacterial foraging algorithm, hybrid software architecture
Recommended Citation
Mueller, C., & Radewagen, R. (2016). Implications For Hybridization of Recommender System and Heuristic Algorithms Based On The Bacterial Foraging Algorithm. IMT Case Journal, 6(1), 1-8. https://jetbm.imtnagpur.ac.in/journal/vol6/iss1/1