Browsing by Author "Kao, Chien-Pang"

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Building a qualitative recruitment system via SVM with MCDM approach
(2011-08-01)
Li, Yung-Ming
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Lai, Cheng-Yang
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Kao, Chien-Pang
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資訊管理與財務金融系註：原資管所+財金所
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Department of Information Management and Finance
Advances in information technology have led to behavioral changes in people and submission of curriculum vitae (CV) via the Internet has become an often-seen phenomenon. Without any technological support for the filtering process, recruitment can be difficult. In this research, a method combining five-factor personality inventory, support vector machine (SVM), and multi-criteria decision-making (MCDM) method was proposed to improve the quality of recruiting appropriate candidates. The online questionnaire personality testing developed by the International Personality Item Pool (IPIP) was utilized to identify the personal traits of candidates and both SVM and MCDM were employed to predict and support the decision of personnel choice. SVM was utilized to predict the fitness of candidates, while MCDM was employed to estimate the performance for a job placement. The results show the proposed system provides a qualified matching according to the results collected from enterprise managers.
TREPPS: A Trust-based Recommender System for Peer Production Services
(2009-03-01)
Li, Yung-Ming
;
Kao, Chien-Pang
;
資訊管理與財務金融系註：原資管所+財金所
;
Department of Information Management and Finance
Peer production, a new mode of production, is gradually shifting the traditional, capital-intensive wealth production to a model which heavily depends oil information creating and sharing. More and more online users arc relying oil this type of services such as news, articles, bookmarks, and various user-generated contents around World Wide Web. However, the quality and the veracity of peers' contributions are not well managed. Without a practical means to assess the quality of peer production services, the consequence is information-overloading. In this study, we present a recommender system based oil the trust of social networks. Through the trust computing, the quality and the veracity of peer production services can be appropriately assessed. Two prominent fuzzy logic applications fuzzy inference system and fuzzy MCDM method are utilized to support the decision of service choice. The experimental results showed that the proposed recommender system can significantly enhance the quality of peer production services and furthermore overcome the information overload problems. In addition, a trust-based social news system is built to demonstrate the application of the proposed system. (C) 2008 Elsevier Ltd. All rights reserved.