• BERT Modeli ile Türkçe Duygu Analizi 

  Acikalin, Utku Umur; Bardak, Benan; Kutlu, Mucahid (Institute of Electrical and Electronics Engineers Inc., 2020-09)

  While sentiment analysis is a popular research area, most of the research has been conducted for English and the number of studies for Turkish are rather limited. Limited resources for Turkish natural language processing ...

• Türkçe Haber Metinleri için Makine Öğrenmesi Temelli Özetleme 

  Kartal, Yavuz Selim; Kutlu, Mucahid (Institute of Electrical and Electronics Engineers Inc., 2020-09)

  In this paper, we propose an automatic text summarization model for Turkish news articles using machine learning models. Our proposed model uses sentence position, speech expression, presence of named entities and statements, ...

• TrClaim-19: The First Collection for Turkish Check-Worthy Claim Detection with Annotator Rationales 

  Kartal, Yavuz Selim; Kutlu, Mücahid (Association for Computational Linguistics, 2020-11)

  Massive misinformation spread over Internet has many negative impacts on our lives. While spreading a claim is easy, investigating its veracity is hard and time consuming, Therefore, we urgently need systems to help human ...

• Nesnelerin İnternetinin Güvenliğinde İnsan Faktörü 

  Tok, Mevlüt Serkan; Selçuk, Ali Aydın (Türkiye Bilişim Vakfı , 2019-12)

  The growing presence of Internet of Things (IoT) devices has not only contributed in digital transformation of industry, transportation, healthcare and many other fields with smart devices producing and sharing data online; ...

• Can Driving Patterns Predict Identity and Gender? 

  Abul, Osman; B. Karatas (Springer Science and Business Media Deutschland GmbH, 2019-09)

  The advances in vehicle equipment technology enabled us easy and large-scale collection of high-volume vehicle driving data. This data is an important resource for urban area traffic management and vehicle driving support ...

• Stock Market Technical Indicator Optimization by Genetic Algorithms 

  Özbayoğlu, Ahmet Murat; Erkut, Umur (ASME Press, 2010)

  Technical indicators are widely used in stock market forecasting, mostly to trigger the buy/sell rules in the technical analysis. Through some statistical analysis some key values for several indicator parameters are ...

• Finansal İşlemler için Evrimsel Hesaplamalar Yoluyla Eğilimden Arındırılmış Bağıl Güç Endeksi Göstergesi 

  Şahin, Uğur; Özbayoğlu, Ahmet Murat (2015)

  Borsa tahmini ve eğilim bulma hem finans profesyonelleri hem de borsa araştırmacılarının yüksek ilgi alanları arasındadır [2]. Hemen herkes, öyle ya da böyle, hisse senedi alım satımları için doğru senetler ve/ veya doğru ...

• Hardgrove Grindability Index Estimation Using Neural Networks 

  Özbayoğlu, Gülhan; Özbayoğlu, Ahmet Murat (2008)

  In a previous study, different techniques for the estimation of coal HGI values were investigated (Özbayoğlu et.al, 2008). As continuation of that research, in this study a revised neural network methodology is used for ...

• Comparison of Bayesian Estimation and Neural Network Model in Stock Market Trading 

  Özbayoğlu, Ahmet Murat; Bahadır, İsmet (ASME Press, 2008)

  In this study, a decision support system for stock market prediction is proposed. This model uses the historical data of 180K data points obtained from the 215 highest volume ETFs that are open for trade in NYSE. The data ...

• Deep Multi-Layer Perceptron based Prediction of Energy Efficiency and Surface Quality for Milling in The Era of Sustainability and Big Data 

  Serın, Gokberk; Sener, Batihan; Gudelek, M. Ugur; Özbayoğlu, Ahmet Murat; Ünver, Hakkı Özgür (Elsevier Ltd, 2020)

  In advanced industries such as aerospace, medical and automotive, high precision machining is increasingly required for many parts made by difficult-to-cut alloys. Machine tool manufacturers respond to this demand by ...

• Predicting the number of bidders in public procurement 

  Gorgun, M.K.; Kutlu, Mücahid; Tas, B.K.O. (Institute of Electrical and Electronics Engineers Inc., 2020-09)

  Public procurement constitutes an important part of economical activities. In order to effectively use public resources, increasing competition among firms participating in public procurement is essential. In this work, ...

• Efficient Test Collection Construction via Active Learning 

  Rahman, M.M.; Kutlu, Mücahid; Elsayed, T.; Lease, M.a (Association for Computing Machinery, 2020-09)

  To create a new IR test collection at low cost, it is valuable to carefully select which documents merit human relevance judgments. Shared task campaigns such as NIST TREC pool document rankings from many participating ...

• A Novel FPGA-Based High Throughput Accelerator for Binary Search Trees 

  Melikoglu, O.; Ergin, Oğuz; Salami, B.; Pavon, J.; Unsal, O.; Cristal, A. (Institute of Electrical and Electronics Engineers Inc., 2019-07)

  This paper presents a deeply pipelined and massively parallel Binary Search Tree (BST) accelerator for Field Programmable Gate Arrays (FPGAs). Our design relies on the extremely parallel on-chip memory, or Block RAMs (BRAMs) ...

• Are we secure from bots? Investigating vulnerabilities of botometer 

  Torusdağ, Buğra M.; Kutlu, Mücahid; Selçuk, Ali Aydın (Institute of Electrical and Electronics Engineers Inc., 2020-09)

  Social media platforms such as Twitter provide an incredibly efficient way to communicate with people. While these platforms have many benefits, they can also be used for deceiving people, spreading misinformation, ...

• Building Test Collections using Bandit Techniques: A Reproducibility Study 

  Altun, Bahadir; Kutlu, Mücahid (Association for Computing Machinery, 2020-10)

  The high cost of constructing test collections led many researchers to develop intelligent document selection methods to find relevant documents with fewer judgments than the standard pooling method requires. In this paper, ...

• An Experimental Study of Reduced-Voltage Operation in Modern FPGAs for Neural Network Acceleration 

  Salami, B.; Onural, E.B.; Yuksel, I.E.; Koc, F.; Ergin, Oğuz; Cristal Kestelman, A.; Unsal, O.; Sarbazi-Azad, H.; Mutlu, O. (Institute of Electrical and Electronics Engineers Inc., 2020-07)

  We empirically evaluate an undervolting technique, i.e., underscaling the circuit supply voltage below the nominal level, to improve the power-efficiency of Convolutional Neural Network (CNN) accelerators mapped to Field ...

• Financial Trading Model with Stock Bar Chart Image Time Series with Deep Convolutional Neural Networks 

  Sezer, Omer Berat; Özbayoğlu, Ahmet Murat (Tech Science Press, 2020)

  Even though computational intelligence techniques have been extensively utilized in financial trading systems, almost all developed models use the time series data for price prediction or identifying buy-sell points. ...

• Deep Learning Based Hybrid Computational Intelligence Models for Options Pricing 

  Arin, Efe; Özbayoğlu, Ahmet Murat (SPRINGER, 2020-11)

  Options are commonly used by traders and investors for hedging their investments. They also allow the traders to execute leveraged trading opportunities. Meanwhile accurately pricing the intended option is crucial to perform ...

• On Existence of Equilibrium Under Social Coalition Structures 

  Çaşkurlu, Buğra; Ekici, Ozgun; Kizilkaya, Fatih Erdem (Springer Science and Business Media Deutschland GmbH, 2020-10)

  In a strategic form game, a strategy profile is an equilibrium if no viable coalition of agents benefits (in the Pareto sense) from jointly changing their strategies. Weaker or stronger equilibrium notions can be defined ...

• Security-Aware Database Migration Planning 

  Subramani, K.; Çaşkurlu, Buğra; Acikalin, U.U. (Springer Science and Business Media Deutschland GmbH, 2020-08)

  Database migration is an important problem faced by companies dealing with big data. Not only is migration a costly procedure, it involves serious security risks as well. For some institutions, the primary focus is on ...

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