Genetic algorithms as a tool for structuring collaborative groups
Natural Computing, ISSN: 1572-9796, Vol: 16, Issue: 2, Page: 231-239
2017
- 17Citations
- 23Captures
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Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
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Article Description
Collaborative learning is a process in which two or more individuals interact in order to learn something. The success of the learning process depends on the way in which the individuals are engaged in a community. Within the community, individuals are grouped into small clusters according to their homogeneous properties and the diversity within the group. In this work we focus on the formation of groups of individuals. More specifically, we apply genetic algorithms in the formation process in order to deal with the high level of complexity. We developed a prototype to evaluate the approach and the results are discussed.
Bibliographic Details
http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=84978036882&origin=inward; http://dx.doi.org/10.1007/s11047-016-9574-1; http://link.springer.com/10.1007/s11047-016-9574-1; http://link.springer.com/content/pdf/10.1007/s11047-016-9574-1; http://link.springer.com/content/pdf/10.1007/s11047-016-9574-1.pdf; http://link.springer.com/article/10.1007/s11047-016-9574-1/fulltext.html; https://dx.doi.org/10.1007/s11047-016-9574-1; https://link.springer.com/article/10.1007/s11047-016-9574-1
Springer Science and Business Media LLC
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