Title :
An Artificial Immune System for job recommendation
Author :
Al-Otaibi, Shaha T. ; Ykhlef, Mourad
Author_Institution :
Coll. of Comput. & Inf. Sci., Princess Nora Bint Abdualrahman Univ., Riyadh, Saudi Arabia
Abstract :
Artificial Immune System is a novel computational intelligence technique inspired by immunology has appeared in the recent few years and takes inspiration from the immune system in order to develop new computational mechanisms to solve problems in a broad range of domain areas. This paper presents a problem oriented approach to design an immunizing solution for job recommendation problem. We will describe the immune system metaphors that are relevant to job recommender system. Then, discuss the design issues that should be taken into account such as, the features of the problem to be modeled, the data representation, the affinity measures, and the immune process that should be tailored for the problem. Finally, the corresponding computational model is presented.
Keywords :
artificial immune systems; data structures; job specification; recommender systems; affinity measures; artificial immune system; data representation; job recommender system; novel computational intelligence technique; problem oriented approach; Cells (biology); Cloning; Immune system; Optimization; Recommender systems; Resumes; Vectors; Affinity measures; Artificial Immune System (AIS); Clonal Selection; Collaborative filtering recommender system; Computational Intelligence (CI); Content-based recommender system; Hybrid based recommender system; Recommender systems; somatic hypermutation;
Conference_Titel :
Bio-inspired Intelligence (IWOBI), 2014 International Work Conference on
Conference_Location :
Liberia
DOI :
10.1109/IWOBI.2014.6913935