Abstract

In this paper, we propose a freelancer matching of a recommended recruitment system in a situation in which the freelance type employment market defined by peer-to-peer transactions, mutual evaluation of freelancers and clients, time flexibility of service providers, and the use of service providers' tools and assets are expanding. In order to increase the reliability and accuracy of recommendation through reputation, we propose a reputation ranking technique for reputation system, which is a kind of personalized recommendation system, based on the blockchain technology. We propose a reputation system model suitable for recruitment matching service. We have aims to study the method of implicitly extracting user reputation information based on two factors suitable for word of mouth among information source reliability factors. In other words, this paper defines a method for automatically extracting two reliability factors of freelancers from past reputation information, and proposes a method for effectively predicting freelancer applicant’ reputation information using only the information of high-reliability evaluators.

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