Abstract
Finding the best solution for an optimization problem is a tedious task, specifically in the presence of enormously represented features. When we handle a problem such as job recommendations that have a diversity of their features, we should rely to metaheuristics. For example, the Artificial Immune System which is a novel computational intelligence paradigm achieving diversification and exploration of the search space as well as exploitation of the good solutions were reached in reasonable time. Unfortunately, in problems with diversity nature such job recommendation, it produces a huge number of antibodies that causes a large number of matching processes affect the system efficiency. To leverage this issue, we present a new intelligence algorithm inspired by immunology based on monoclonal antibodies production principle that, up to our knowledge, has never applied in science and engineering problems. The proposed algorithm recommends ranked list of best applicants for a certain job. We discussed the design issues, as well as the immune system processes that should be applied to the problem. Finally, the experiments are conducted that shown an excellence of our approach.
Highlights
The Job Recommender System (JRS) has emerged in ebusiness online services in recent years
We proposed an algorithm for JRS that used the traditional Artificial Immune System (AIS) paradigm [3]
We start by describing the metaphors and the parameters that used in MCAIS-JRS algorithm, where the antibody is a certain job's feature and the antigen is a vector of features for an applicant that considered as a target to be checked
Summary
The Job Recommender System (JRS) has emerged in ebusiness online services in recent years. When we handle a problem such as job recommendations with a diverse nature in their features, the traditional AIS produced a huge number of antibodies that affects the system efficiency. The AIS applied the mutation strategy to perform the diversity topic in the previous algorithm To leverage this issue, we will apply the AIS with Monoclonal Antibodies (MAbs) production principle that produces a population of antibodies from a single B-cell that recognize the antigen. The algorithm that we will propose in this article is named Monoclonal Artificial Immune System for Job Recommender System (MCAIS-JRS). It recommends ranked list of best applicants for a certain job.
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More From: International Journal of Advanced Computer Science and Applications
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