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EVALUATION OF PERFORMANCE METRICS USED IN RECOMMENDATION SYSTEMS ACCORDING TO FILTERING TECHNOLOGIES: A RESEARCH STUDY ON THE FIELD OF JOB RECOMMENDATION SYSTEMS

Year 2024, , 706 - 725, 03.09.2024

Selin Bitirim , Duygu Çelik Ertuğrul

https://doi.org/10.17780/ksujes.1410926

Abstract

Thanks to Recommendation Systems (RSs), it has become possible to carry out existing processes/operations effectively in almost every sector (e.g. e-commerce, education, entertainment, healthcare, human resources, advertising, etc.) and to prioritize items that may interest the user. With the contribution of RSs, it is possible to effectively manage sectoral processes/services and produce personalized results for users. This study aims to review RS-related research, reveal a taxonomy of filtering techniques, and identify widely encountered performance metrics. In addition, Job Recommendation Systems, which are indispensable for Human Resources (HR) management, were chosen as the research area in this study and it was planned to determine performance metrics and item filtering approaches. Various studies from the literature on RS architecture and solutions, conducted between 2010 and 2023, were selected according to their relevance and reviewed. Filtering techniques in RSs are classified hierarchically and the majority evaluation metrics used in performance evaluations are determined and categorized. Additionally, the reflections of the gains learned from RSs on Job Recommendation Systems were investigated and RS solutions/metrics in the field of HR were presented. Finally, this study serves as a road map for researchers who want to conduct research, development and quality evaluations on RS solutions.

Keywords

Recommender systems job recommender systems taxonomy filtering performance metrics

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ÖNERİ SİSTEMLERİNDE KULLANILAN PERFORMANS METRİKLERİNİN FİLTRELEME TEKNOLOJİLERİNE GÖRE DEĞERLENDİRİLMESİ: İŞ ÖNERİ SİSTEMLERİ ALANI ÜZERİNE BİR ARAŞTIRMA ÇALIŞMASI

Year 2024, , 706 - 725, 03.09.2024

Selin Bitirim , Duygu Çelik Ertuğrul

https://doi.org/10.17780/ksujes.1410926

Abstract

Tavsiye Sistemleri (Recommendation Systems—RSs) sayesinde hemen hemen her sektörde (ör. e-ticaret, eğitim, eğlence, sağlık, insan kaynakları, reklamcılık, vb.) mevcut süreçlerin/operasyonların etkin bir biçimde yürütülebilmesi ve kullanıcının ilgisini çekebilecek öğelere öncelik verilmesi mümkün hale gelmiştir. RS'lerin katkısı ile, sektörel süreçlerin/hizmetlerin etkin şekilde yönetilmesi ve kullanıcılara kişiselleştirilmiş sonuçlar üretilmesi mümkündür. Bu çalışmada, RS ile ilgili araştırmaların gözden geçirilmesi, filtreleme teknikleri taksonomisinin ortaya çıkarılması ve geniş çapta rastlanan performans metriklerinin tespiti amaçlanmaktadır. Ayrıca, İnsan Kaynakları (İK) yönetiminin olmazsa olmazı olan İş Tavsiye Sistemleri bu çalışmada, araştırma sahası olarak seçilmiş olup performans metriklerinin ve öğe filtreleme yaklaşımlarının belirlenmesi planlanmıştır. RS mimarisi ve çözümleri üzerine, literatürden 2010-2023 yılları arasında yapılmış çeşitli çalışmalar ilgililik durumuna göre seçilmiş ve incelenmiştir. RS’lerde filtreleme teknikleri hiyerarşik olarak sınıflandırılmış ve performans değerlendirmelerinde kullanılan çoğunluk değerlendirme metrikleri saptanarak kategorize edilmiştir. Ayrıca, RS'lerden öğrenilen kazanımların İş Tavsiye Sistemleri’ndeki yansımaları araştırılmış ve IK alanındaki RS çözümleri/metrikleri ortaya konulmuştur. Son olarak, RS çözümleri üzerinde araştırma, geliştirme ve kalite değerlendirmeleri yapmak isteyen araştırmacılara, bu çalışmamız bir yol haritası niteliğindedir.

Keywords

Tavsiye Sistemleri İş Tavsiye Sistemleri Taksonomi Filtreleme Performans Metrikleri

Ethical Statement

Etik onay beyanı: Bu çalışma için resmi onay gerekli değildir.

Supporting Institution

DOĞU AKDENİZ ÜNİVERSİTESİ

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There are 77 citations in total.

Details

Primary Language Turkish
Subjects Business Process Management, Decision Support and Group Support Systems, Information Systems (Other), Performance Evaluation
Journal Section Computer Engineering
Authors

Selin Bitirim 0000-0002-3575-5855

Duygu Çelik Ertuğrul 0000-0003-1380-705X

Publication Date September 3, 2024
Submission Date December 27, 2023
Acceptance Date February 17, 2024
Published in Issue Year 2024

Cite

APA Bitirim, S., & Çelik Ertuğrul, D. (2024). ÖNERİ SİSTEMLERİNDE KULLANILAN PERFORMANS METRİKLERİNİN FİLTRELEME TEKNOLOJİLERİNE GÖRE DEĞERLENDİRİLMESİ: İŞ ÖNERİ SİSTEMLERİ ALANI ÜZERİNE BİR ARAŞTIRMA ÇALIŞMASI. Kahramanmaraş Sütçü İmam Üniversitesi Mühendislik Bilimleri Dergisi, 27(3), 706-725. https://doi.org/10.17780/ksujes.1410926