Exploring the Journals using Artificial Bee Colony algorithm

Abstract: The assessment of academic journals is a critical task to numerous scientific actions. These assessments may have an important influence on various issues reaching from publishing articles in academic journals to determining. The main aim is to develop the system that have the fair means of the selection of the best journal. Here we propose the system for ranking the journals in a huge data set which may include both similar and dissimilar distances of values from which the effective means of results being declared. A method for exploring the journals using, Artificial Bee Colony algorithm is presented to lessen the effort in working with the growth of data volumes. Artificial Bee Colony (ABC) is introduced for web mining for the both Journal Citation Reports and proposed data sets. This algorithm results us with relevant information for the questions posted by the clients when related to present Fuzzy c-means algorithm.

Keywords: Citation, Impact factor, Eigen factor, Artificial Bee colony.