The Study Of Electronic Business Recruitment System Based On Web

With the rapid development of Web information technology and the general application of management information system in various industries,it is an important factor to restrict the survival and development of enterprises whether to complete the transformation of application system informatization and intelligence with the help of new technology in the shortest time.Because of its characteristics of openness,normalization,high display and fast update,the traditional talent recruitment information system has been unable to meet the above functional requirements.Therefore,it is urgent to combine web information technology with e-commerce system of talent recruitment,so as to improve its attention and browsing.In the face of the increasing demand for information,customers not only put forward higher requirements for timely and accurate information,accurate recommendation of reasonable recruitment enterprises,recruitment information to meet the security requirements,but also need the system to be able to successfully complete the basic functional modules such as adding,deleting,modifying and checking,so as to improve the attention of talent recruitment information,improve recruitment efficiency and save.Recruitment cost,reduce the fatigue of personnel who publish recruitment information.The e-commerce system of talent recruitment can realize the functions of new user registration,recruitment information cluster analysis,accurate directional recommendation according to the situation of candidates and background information maintenance of general talent recruitment system.This paper proposes an improved intelligent optimization algorithm based on which the recruitment system and importance ranking are mapped into gene chains respectively.Aiming at the highest satisfaction of candidates and the high updating speed of recruitment information,it proposes a double chain coding strategy of rational information ranking chain and publishing information classification chain.It also proposes an improved algorithm based on cloud intelligent optimization and cloud crossover and mutation.The method which is proposed to prevent the solution from premature convergence or convergence can obtain the local optimal solution.Finally,the effectiveness and efficiency of this method are verified by a real case.