Natural Language Processing (NLP) is a subfield of Artificial Intelligence and Linguistics. However, due to significant advancements in the field of computing, NLP has become a discipline considered independently today, making research areas within NLP popular.

Language ability is unique to humans, which is why linguistics holds an important place within Cognitive Sciences. NLP deals with problems related to the generation and understanding of natural languages by computers. If a model of the language can be created in a computer environment, it would be an extremely useful tool for communication.

The main task of NLP is to design and implement computer systems that can analyze, understand, interpret, and generate a natural language. Research areas within NLP include a better understanding of the structure of natural languages, using natural language as an interface between computers and humans, and performing computer-based language translation. All the work done in this field has been developed for English, a valid language in science and business. Directly translating the rules and algorithms used for English into Turkish is not very feasible due to the morphological differences between the languages. Therefore, studies to be conducted for Turkish can only be carried out by Turkish linguists or native or foreign computer engineers who know Turkish very well.

Applications of NLP include word processors, querying databases using natural language instead of SQL and converting these queries into SQL to provide the result to the user, semi-automatic text translation from one language to another, accessing single or multilingual dictionaries, generating sentences and texts in natural language, summarizing texts, speech recognition, and speech synthesis.

Our Natural Language Research group strives to provide solutions to problems with Machine Learning and Deep Learning-based approaches. In addition to applying existing algorithms to current problems, we design and develop projects aimed at academia and industry by developing new algorithms and approaches.

Our Natural Language Processing Research group is in the establishment phase and welcomes researchers and students who want to work on natural language processing and data science. Studies conducted and planned to be conducted will soon be shared here.

Below are details of the studies carried out and completed by the research group. In addition to ongoing master's and doctoral theses, scientific articles, presentations, and project works are actively conducted. Updates will be announced on the research group page as they are completed.

For information: [email protected]

Team Members

• Assoc. Prof. Dr. Metin Bilgin
• Research Assistant Büşra Çantaoğlu (Computer Engineering Master's Student)
• Melek Turan (Computer Engineering Master's Student)
• Zafer Onan (Computer Engineering Master's Student)
• Mustafa Saygın (Computer Engineering Master's Student)
• Bahadır Özen (Computer Engineering PhD Student)
• Lecturer Murat Eser (Computer Engineering PhD Student)
• Lecturer Engin Demir (Computer Engineering PhD Student)
• Mehmet Bozdemir (Computer Engineering PhD Student)
• Yavuz Selim Bakan (Computer Engineering PhD Student)

Produced Theses

• Analysis of CPU and GPU Performance of Clustering Algorithms - Master's Thesis - Melek Güler - 2022
• Creating Python Syntax for Turkish Verbal Expressions Using Machine Translation - Master's Thesis - Mehmet Bozdemir - 2022
• Investigating the Effect of Rating Training Samples in Deep Learning Algorithms - Master's Thesis - Kaan Karaköse - 2022
• Performance Analysis of Contextual Vectors in the Visual Question Answering Problem - Master's Thesis - Özlem Hakdağlı - 2022
• Solution of the Vehicle Routing Problem with a Heterogeneous Fleet Using a Hybrid Approach - Master's Thesis - Nisanur Bulut - 2020
• Deep Learning-Based Transparent Object Recognition - Master's Thesis - Korhan Mutludoğan - 2020

Produced Publications

• Research on Behavior of Two New Random Entity Mobility Models in 3-D Space, M Bilgin, M Eser, Arabian Journal for Science and Engineering 47 (2), 1159-1171, 2022.
• Compatibility Themed Solution of the Vehicle Routing Problem on the Heterogeneous Fleet, M Bilgin, N Bulut, International Arab Journal of Information Technology 19 (5), 774-784, 2022. 
• Detecting transparency of glasses with capsule networks based on deep learning, M Bilgin, K Mutludoğan, 6th International Conference on Computer Science and Engineering (UBMK), 2021.
• A New Approach to Automatically Find and Fix Erroneous Labels in Dependency Parsing Treebanks, M Bilgin, International Arab Journal of Information Technology 18 (3), 356-364, 2021. 
• Güzergah Belirleme Yöntemi, M Bilgin, TR Patent 2019/14,532, 2021. 
• A new statistics-based approach to improve Word2Vec's sentiment classification success, M Bilgin, Selcuk University Journal of Engineering Sciences 20 (3), 63-72, 2021.
• A New Approach Based on Simulation of Annealing to Solution of Heterogeneous Fleet Vehicle Routing Problem, M Bilgin, N Bulut, International Conference on Artificial Intelligence and Applied Mathematics in Engineering, 2021.
• A new strategy for curriculum learning using model distillation, K Karaköse, M Bilgin, Global Journal of Computer Sciences: Theory and Research 10 (2), 57-65, 2020.
• Classsification of Turkish Tweets by Document Vectors and Investigation of the effects of parameter changes on classification success, M Bilgin, Sigma Journal of Engineering and Natural Sciences 38 (3), 1581-1592, 2020.
• Mobil Kitle Algılamada Mesaj Gecikme Zamanı Üzerine Bir Araştırma, M Bilgin, Dokuz Eylül Üniversitesi Mühendislik Fakültesi Fen ve Mühendislik Dergisi, 22 (65), 393-400, 2020.
• Novel random models of entity mobility models and performance analysis of random entity mobility models, M Bilgin, TURKISH JOURNAL OF ELECTRICAL ENGINEERING & COMPUTER SCIENCES 28 (2), 708-726, 2020.
• Danışmanlı ve yarı danışmanlı öğrenme kullanarak doküman vektörleri tabanlı tweetlerin duygu analizi, M Bilgin, İF Şentürk, Balıkesir Üniversitesi Fen Bilimleri Enstitüsü Dergisi 21 (2), 822-839, 2020.
• American sign language character recognition with capsule networks, M Bilgin, K Mutludoğan, 3rd International Symposium on Multidisciplinary Studies and Innovative Technologies (ISMSIT), 2019.
• Sentiment analysis of tweets based on document vectors using supervised learning and semi-supervised learning, M Bilgin, İF Şenturk, Journal of Balıkesir University Institute of Science and Technology, 21(2), 822-839, 2019.
• Sentiment Analysis with Term Weighting and Word Vectors, M Bilgin, H Köktaş, International Arab Journal of Information Technology 16 (5), 953-959, 2019.
• A Study on Named Entity Recognition with OpenNLP at English Texts, M Bilgin, Journal of Applied Intelligent System 4 (1), 1-8, 2019.
• Kelime Vektörü Yöntemlerinin Model Oluşturma Sürelerinin Karşılaştırılması, M BİLGİN, Bilişim Teknolojileri Dergisi 12 (2), 141-146, 2019.
• Türkçe Metinlerin Sınıflandırma Başarısını Artırmak için Yeni Bir Yöntem Önerisi, M BİLGİN, Uludağ University Journal of The Faculty of Engineering 24 (1), 125-136, 2019.
• C# ile Nesne Tabanlı Programlama, M Bilgin, M Eser, Kodlab, 2018.
• Makine Öğrenmesi Teorisi ve Algoritmaları, M Bilgin, Papatya Bilim, 2018.
• Identification of Vehicle Design and Transition of Traffic Signs with Image Processing Method, M BILGIN, Z ZEYBEK, International Journal of Electronics, Mechanical and Mechatronics Engineering (IJEMME), 8(2), 1555-1569, 2018.
• Sentiment analysis on Twitter data with semi-supervised Doc2Vec, M Bilgin, İF Şentürk, 2017 international conference on computer science and engineering (UBMK), 661-666, 2017.
• Gerçek Veri Setlerinde Klasik Makine Öğrenmesi Yöntemlerinin Performans Analizi, M Bilgin, Akademik Bilişim Konferansı, 2017.
• Word2Vec Based Sentiment Analysis for Turkish Texts, M Bilgin, H Köktaş, International Conference on Engineering Technologies, Konya, Turkey, 106-109, 2017.
• Dependency parsing with stacked conditional random fields for Turkish, M Bilgin, M Amasyalı, Journal of the Faculty of Engineering and Architecture of Gazi University 32 (2), 2017.
• Semantic role labeling with relative clauses, M BİLGİN, MF AMASYALI, International Journal of Electronics Mechanical and Mechatronics Engineering, 6(2), 1165-1175, 2016.
• Comparison of Machine Learning Methods for the Sequence Labelling Applications, MF AMASYALI, M BİLGİN, 23nd Signal Processing and Communications Applications Conference, 503-506, 2015.
• Bileşik Cümlelerde Yan Cümleciklerin Otomatik Etiketlenmesi, M BİLGİN, MF AMASYALI, Akademik Bilişim, 2015.

Former Members

Kaan Karaköse (Computer Engineering Master's Graduate)  
Korhan Mutludoğan (Computer Engineering Master's Graduate)  
Nisanur Bulut (Computer Engineering Master's Graduate)  
Özlem Hakdağlı (Computer Engineering Master's Graduate)  
Melek Güler (Computer Engineering Master's Graduate)