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Bu bildiride mavi yakalı iş arama ve bulma platformu olan İşin Olsun sitesindeki ilanların içerik yönetimi ve otomatik içerik kontrolü hakkında geliştirilen yaklaşımlar açıklanacaktır. Bu amaçla denetimli makine öğrenmesi modelleri ve Bert transformer mimarisi yöntemleri ile deneyler gerçekleştirilerek sonuçları gözlemlenmiştir. Çalışma sonunda, en başarılı yöntem Bert for sequence classification kullanılarak ilan içeriklerinin otomatik olarak sınıflandırıldığı bir sistem geliştirilmiş ve bu sistem iş arama platformuna entegre edilmiştir. İşin Olsun ilan metinlerinin kontrolör görevindeki kişiler tarafından uygun veya uygun olmayan içerik şeklinde iki farklı sınıfta etiketlenmesinden başlayarak, veri kümesinin hazırlanma aşamalarından, sınıflandırma modelinin sisteme entegrasyonuna kadar olan çalışmalar bu bildiride özetlenmektedir.
This notice will describe the approaches developed to the content management and automatic content control of the Advertisements on the site, the blue-fledged job search and search platform. For this purpose, the results were observed by conducting experiments with controlled machine learning models and Bert transformer architecture methods. At the end of the study, the most successful method was developed a system where advertising content was automatically classified using Bert for sequence classification and this system was integrated into the job search platform. Starting from the labelling of the text of the publication in two different classes in the form of appropriate or inappropriate content by persons in the controller's task, the work from the preparation stages of the data set to the integration of the classification model into the system is summarized in this statement.
In this paper, the approaches developed for the content management and automatic content control of the postings on the İşin Olsun website, which is a blue-collar job search and finding platform, will be explained. For this purpose, experiments were carried out with supervised machine learning models and Bert transformer architecture methods and the results were observed. At the end of the study, a system was developed in which the contents of the job texts are automatically classified using Bert for sequence classification, which was determined as the most successful method, and this system was integrated into the job search platform. Starting from labeling the job texts in two different classes as appropriate or unsuitable content by the controllers, from the preparation stages of the dataset to the integration of the classification model into the system, the studies are summarized in this paper.
Alan : Mühendislik
Dergi Türü : Ulusal
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