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Yayın Bibliometric Analysis of the Tertiary Study on Agile Software Development using Social Network Analysis(Institute of Electrical and Electronics Engineers Inc., 2020) Bayram, E.; Dogan, B.; Tunali, V.This study aims to examine the systematic literature reviews published on the Agile Software Development subject between 2013 and 2018 and to examine the citation relationships among the studies within the scope of the tertiary study with the help of social network analysis. In this study, the publications within the scope were visualized with VOSviewer and Gephi social network analysis tools, and the relations between publishing institutions, countries were revealed. In citation analysis; according to the total link strength, it is seen that UK, Spain and Slovenia are at the forefront at institution and country level. Brazil has the highest citation value and provides the link between the two large clusters obtained in the analysis. In the bibliographic coupling analysis, the five most active countries at the country level were Brazil, Germany, Finland, Malaysia and Pakistan. When the same analysis is made at the institution level, the top five institutions are in Brazil, Switzerland, Peru and Pakistan. The findings of the study indicate that developing countries have more studies on the subject and that the cited publications are mostly from developed countries; European countries seem to be more collaborative based on citation analysis yet developing countries such as Brazil and Malaysia have also relations with them; the number of publications is not directly proportional to the citations. © 2020 IEEE.Yayın An improved clustering algorithm for text mining: Multi-cluster spherical K-means(Zarka Private Univ, 2016) Tunali, V.; Bilgin, T.; Camurcu, A.Thanks to advances in information and communication technologies, there is a prominent increase in the amount of information produced specifically in the form of text documents. In order to, effectively deal with this “information explosion” problem and utilize the huge amount of text databases, efficient and scalable tools and techniques are indispensable. In this study, text clustering which is one of the most important techniques of text mining that aims at extracting useful information by processing data in textual form is addressed. An improved variant of spherical K-Means (SKM) algorithm named multi-cluster SKM is developed for clustering high dimensional document collections with high performance and efficiency. Experiments were performed on several document data sets and it is shown that the new algorithm provides significant increase in clustering quality without causing considerable difference in CPU time usage when compared to SKM algorithm. © 2016, Zarka Private Univ. All rights reserved.Yayın PRETO: A high-performance text mining tool for preprocessing Turkish texts(2012) Tunali, V.; Bilgin, T.T.Text documents are usually unstructured and written in natural language. To apply conventional data mining techniques on text documents, a preprocessing operation is indispensable. In this paper, we introduce PRETO, a cross-platform, powerful and scalable preprocessing tool developed specifically for preprocessing Turkish texts, with a wide range of preprocessing options like stemming, stopword filtering, statistical term filtering, and n-gram generation. We demonstrate the performance and scalability of PRETO with some experiments on large document collections. Copyright ©2012 ACM.Yayın Text mining and social network analysis on computer science and engineering theses in Turkey(Association for Computing Machinery, 2014) Tunali, V.; Bilgin, T.T.In this study, we examined 6,834 master's and PhD theses conducted on computer science and engineering between 1994 and 2013 in Turkey. Thesis data were compiled from the YÖK national thesis database web portal. We used text mining techniques to extract research concepts and their co-occurrence data from graduate thesis abstracts. Then, we applied social network analysis techniques on the concept cooccurrence networks to visually explore core research concepts, and connections and relationships among them. We showed that text mining and social network analysis techniques together were very effective for knowledge discovery in scientific documents in computer science and engineering domain. Copyright © 2014 ACM.Yayın Transfer Learning Approach to COVID-19 Prediction from Chest X-Ray Images(Institute of Electrical and Electronics Engineers Inc., 2021) Bıçakcı, K.; Tunali, V.All countries and societies have been severely affected by the COVID-19 pandemic in many several different ways especially in sectors like healthcare, education, tourism, and so on. During this period, researchers all over the world have been conducting studies, investigating and developing techniques to solve the problems caused by the pandemic. In this work, making use of real-world images, we applied Convolutional Neural Networks to chest X-ray images to predict whether a patient has COVID-19, Viral Pneumonia, or no infection. Initially, we utilized transfer learning to fine tune a number of pre-trained DenseNet, Inception-v3, Inception-ResNet-v2, ResNet, VGG, and Xception models, which are very well-known architectures due to their success in image processing tasks. While the achieved performance with these models was encouraging, we ensembled three models to obtain more accurate and reliable results. Finally, our ensemble model outperformed all other models with an F -Score of 99%. © 2021 IEEE.
