Browsing by Author "Görür, A.K."

Now showing 1 - 4 of 4

Citation - WoS: 6
Citation - Scopus: 8
A Real Time Data Warehouse Approach for Data Processing
(Ieee, 2013) Obali, M.; Görür, Abdül Kadir; Dursun, B.; Erdem, Z.; Görür, A.K.; 107251; Bilgisayar Mühendisliği
Data that is acquired from different data sources needs too much processing for managing, analyzing and monitoring. Also, you have to fuse and exploit efficiently these data and display the results. Data warehouse consolidates data coming from different data sources. A real time data warehouse is used same purpose as data warehouse, in addition to these, data streams into real time data warehouse on time. Therefore, real time data warehouses can be used in many different areas, such as signal processing, data analysis. In this study, we proposed and implement a real time data warehouse using web services as a prototype. © 2013 IEEE.
Citation - Scopus: 4
Deep learning methods with pre-trained word embeddings and pre-trained transformers for extreme multi label text classification
(Institute of Electrical and Electronics Engineers Inc., 2021) Erciyes, N.E.; Görür, A.K.
In recent years, there has been a considerable increase in textual documents online. This increase requires the creation of highly improved machine learning methods to classify text in many different domains. The effectiveness of these machine learning methods depends on the model capacity to understand the complex nature of the unstructured data and the relations of features that exist. Many different machine learning methods were proposed for a long time to solve text classification problems, such as SVM, kNN, and Rocchio classification. These shallow learning methods have achieved doubtless success in many different domains. For big and unstructured data like text, deep learning methods which can learn representations and features from the input data wtihout using any feature extraction methods have shown to be one of the major solutions. In this study, we explore the accuracy of recent recommended deep learning methods for multi-label text classification starting with simple RNN, CNN models to pretrained transformer models. We evaluated these methods' performances by computing multi-label evaluation metrics and compared the results with the previous studies. © 2021 IEEE
Citation - Scopus: 4
Plagiarism detection in learning management system
(Institute of Electrical and Electronics Engineers Inc., 2017) Sabonchi, A.K.S.; Görür, A.K.
Learning Management Systems has become one of the teaching tool same as the pen, pencil, blackboard, book, and notebook. Learning Management System (LMS) is defined and types that are derived from this system such as those focused only on the curriculum and those focuses on the management of the education system, and the combination of both are explained. The properties and features that must exist are identified and showed so that it can be called a learning management system. The name and the experiences of countries in terms of the use of this system as well as the benefits resulting from the user experiences have motivated schools and educational institutions to start the establishment of such systems. The main purpose of this study is, an online plagiarism detection system will be developed and integrated into Moodle so that it can be used by teachers to detect cheating and plagiarism cases in students submitted answers. © 2017 IEEE.
Citation - Scopus: 0
Yazılım geliştirme üretkenliğini etkileyen faktörlerin açımlayıcı faktör analizi yöntemi kullanılarak incelenmesi
(CEUR-WS, 2014) Yilmaz, M.; Yılmaz, Murat; O'Connor, R.V.; Görür, A.K.; Yazılım Mühendisliği