Newaz, S.M SaifPieta, Maliha AnjumAhmed, Mehreen2016-01-192016-01-192015-12ID 10201028ID 09201009ID 11201010http://hdl.handle.net/10361/4892This thesis report is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2015.In this paper we propose a ranking algorithm, HybridABC that is built on swarm based algorithm. In our proposed HybridABC algorithm we merged Artificial Bee Colony (ABC) algorithm with Differential Evolution (DE) algorithm. The ABC is a swarm-based metaheuristic algorithm inspired by the intelligent foraging pattern of bees and Differential Evolution is a population-based stochastic search technique. The proposed implementation of ABC has been tested using the LETOR dataset, which is a standard benchmark dataset for evaluating ranking functions. Our results display that our proposed HybridABC can compete and in many cases more efficient than other state-of-the-art algorithm proposed in ranking web pages based on Genetic Algorithm (GA).enComputer science and engineeringHybridABCLearning a ranking function for information retrieval using HybridABCThesis