Grouping Optimization Based on Social Relationships
Author
Source
Mathematical Problems in Engineering
Issue
Vol. 2012, Issue 2012 (31 Dec. 2012), pp.1-19, 19 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2012-02-06
Country of Publication
Egypt
No. of Pages
19
Main Subjects
Abstract EN
Grouping based on social relationships is a complex problem since the social relationships within a group usually form a complicated network.
To solve the problem, a novel approach which uses a combined sociometry and genetic algorithm (CSGA) is presented.
A new nonlinear relation model derived from the sociometry is established to measure the social relationships, which are then used as the basis in genetic algorithm (GA) program to optimize the grouping.
To evaluate the effectiveness of the proposed approach, three real datasets collected from a famous college in Taiwan were utilized.
Experimental results show that CSGA optimizes the grouping effectively and efficiently and students are very satisfied with the grouping results, feel the proposed approach interesting, and show a high repeat intention of using it.
In addition, a paired sample t-test shows that the overall satisfaction on the proposed CSGA approach is significantly higher than the random method.
American Psychological Association (APA)
Chen, Rong-Chang. 2012. Grouping Optimization Based on Social Relationships. Mathematical Problems in Engineering،Vol. 2012, no. 2012, pp.1-19.
https://search.emarefa.net/detail/BIM-1001371
Modern Language Association (MLA)
Chen, Rong-Chang. Grouping Optimization Based on Social Relationships. Mathematical Problems in Engineering No. 2012 (2012), pp.1-19.
https://search.emarefa.net/detail/BIM-1001371
American Medical Association (AMA)
Chen, Rong-Chang. Grouping Optimization Based on Social Relationships. Mathematical Problems in Engineering. 2012. Vol. 2012, no. 2012, pp.1-19.
https://search.emarefa.net/detail/BIM-1001371
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1001371