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Multi-sided matching lecture allocation mechanism

  • Yoshihito Saito
  • , Takayuki Fujimoto
  • , Tokuro Matsuo

研究成果: 書籍/レポート タイプへの寄稿

抄録

Elective Subject is one of important issues as education program in University. Students can declare their preferences directly by selecting it. In most of university, to allocate elective subjects to the students, university staffs poll students the lectures they want to take. However, due to the limitation of time and number of staffs, the hearing investigation includes the reason and the intention in which students select the lectures. Some students sometimes take a lecture for their career, for academical interest, and for assimilation of knowledge. However, some students might take the lecture following the crowd and take the lecture as Mickey Mouse. The latter case is undesirable for the higher education. To solve the problem, in this paper, we propose a new multi-step lecture allocation method based on students preferences and university intentions. Our protocol consists of the three steps of negotiations and three types of allocations. (1) The university warns the students who have never take a certain compulsory subject yet. The students can choose whether they attend the lecture or not. If the students answer they attend the lecture, the students are allocated to the lecture by priority. (2) The students inform the university of their reasons to take the lecture. The university allocates the lectures to the students based on their reasons. (3) They negotiate about the exchange of lectures to increase students' utilities with each student. Our protocol realizes the high performance of allocation compared with brute force algorithm and reducing computational costs compared with optimizations.

本文言語英語
ホスト出版物のタイトルNew Challenges in Applied Intelligence Technologies
編集者Radoslaw Katarzyniak
ページ299-308
ページ数10
DOI
出版ステータス出版済み - 2008
外部発表はい

出版物シリーズ

名前Studies in Computational Intelligence
134
ISSN(印刷版)1860-949X

All Science Journal Classification (ASJC) codes

  • 人工知能

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