New Artificial Immune System Approach Based on Monoclonal Principle for Job Recommendation

摘要: Finding the best solution for an optimization problem is a tedious task, specifically in presence of enormously represented features. When we handle such as job recommendations that have diversity their features, should rely to metaheuristics. For example, Artificial Immune System which novel computational intelligence paradigm achieving diversification and exploration search space well exploitation good solutions were reached reasonable time. Unfortunately, problems with nature recommendation, it produces huge number antibodies causes large matching processes affect system efficiency. To leverage this issue, present new algorithm inspired by immunology based on monoclonal production principle that, up our knowledge, has never applied science engineering problems. The proposed recommends ranked list applicants certain job. We discussed design issues, immune be problem. Finally, experiments are conducted shown excellence approach.