Ekip Oluşturma Sorunlarına Yönelik Makine Öğrenimi Uygulamalarına İlişkin Sistematik Bir Literatür Taraması

Year 2024, , 175 - 188, 31.07.2024

Soner Karataş , Hüseyin Çakır

https://doi.org/10.17671/gazibtd.1414527

Abstract

Teknolojinin gelişmesiyle birlikte herhangi bir sürece ait tutulan veri çeşitliliği, veri sayısı katlanarak arttı. Bu verilerin işlenmesi ve analiz edilmesiyle bir çok problemin çözümü mümkün olabilmektedir. Ekip tarafından gerçekleştirilen faaliyetlerde en uygun ekip üyesinin seçimi ve doğru ekip oluşumu ekip çalışması başarısını ve sonucunu etkileyen unsurdur. Bu nedenle ekip üyesi seçimi, takım oluşturma problemi son yıllarda artan araştırma konularında biri olmuştur. Farklı disiplinlerden araştırmacılar, başarılı bir ekip oluşturma sürecini sağlayabilmek için araçlar, teknikler ve metodolojiler geliştirmeye çalışmaktadırlar. Makine Öğrenmesi (ML) yöntemleri takım oluşumu, ekip üyesi seçimi problemlerinde son yıllarda kullanılmaya başlayan yöntemlerden biri olmuştur. Bu problemin başarılı sonucu verilerin doğru bir şekilde toplanması, işlenmesi ve uygun makine öğrenme yöntemlerinin seçimine bağlıdır. Bu makalenin amacı takım oluşumu, ekip üyesi seçimi problemlerinde uygulanan makine öğrenme yöntemlerinin sistematik bir literatür taramasını sunmak, bu alanda hangi makine öğrenme metodlarının uygulandığını ve bunların performansını göstermektir. Altı bilimsel veri tabanında konuyla ilgili makaleler araştırılmıştır. Bu inceleme ML yöntemleri hakkında temel bilgiler sağlamanın yanısıra takım oluşumu problemlerinde yeni araştırma çalışmalarını da desteklemektedir.

Keywords

Takım oluşumu, Oyuncu Seçimi, Makine Öğrenimi, Sistematik Literatür Taraması

A Systematic Literature Review of Machine Learning Applications for Team Formation Problems

Abstract

With the development of technology, the variety and number of data held for any process has increased exponentially. By processing and analyzing this data, it is possible to solve many problems. Selection of the most appropriate team member and correct team formation in the activities carried out by the team are the factors that affect the success and result of teamwork. For this reason, the problem of team member selection and team formation has become one of the increasing research topics in recent years. Researchers from different disciplines are trying to develop tools, techniques and methodologies to ensure a successful team building process. Machine Learning (ML) methods have become one of the methods that have started to be used in team formation and team member selection problems in recent years. The successful outcome of this problem depends on the correct collection and processing of data and the selection of appropriate machine learning methods. The aim of this article is to present a systematic literature review of machine learning methods applied in team formation and team member selection problems, and to show which machine learning methods are applied in this field and their performance. Articles on the subject were searched in six scientific databases. In addition to providing fundamental information about ML methods, this review also supports new research efforts on team formation problems.

Keywords

Team formation, Player Selection, Machine Learning, Systematic Literature Review

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