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Customizing Intelligent Recommendation Study with Multiple Advisors Based on Hierarchy Structured Fuzzy‐analytic Hierarchy Process by Wan Park, Seong; Mesicek, Libor; Shin, Joohyun; Bae, Kitae; An, Kyungjin; Ko, Hoon is a Computer Science article available to read on EtoBox.

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## Summary Evaluation information generated by various users is processed using various requirements and data to make recommendations for solving the problems, and it analyzes satisfaction with the results. Despite people normally utilizes the processed information for decision making, not all information, however, brings positive outcomes to users. There are some users who perceived it negatively. In order to minimize the occurrence of such negative effects, the analysis of various user requirements is essential as well as diversifying user inputs for each requirement. Consequently, the results from individual inputs must be predicted. In the past, since the system relies on a single‐expert system, it is necessary to accept and process various limitations of recommendation and multiple requirements. Therefore, the results of the recommendation also have various problems. In order to solve this problem, this study applied an analytic hierarchy process to multiadvisor configuration. In the proposed system, one or multiple advisors are defined, and after analyzing the predefined requirements, the system accepts only the requirements that can be processed and calculates the individual

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Author

Wan Park, Seong; Mesicek, Libor; Shin, Joohyun; Bae, Kitae; An, Kyungjin; Ko, Hoon

Publisher

John Wiley and Sons; Wiley (John Wiley & Sons); John Wiley & Sons Inc.; Wiley (ISSN 1532-0626)

Published

2020

Language

EN

Field

Computer Science (Physical Sciences)