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| − | <p class=" | + | <p class="is-small is-uppercase has-text-weight-bold" style="color: #e0470d;">Track</p> |
| − | <p class=" | + | <p class="title is-3">Data Mining and Machine/Deep Learning</p> |
| − | <p class=" | + | <p class="is-small is-uppercase has-text-weight-bold" style="color: #e0470d;">Track Chair</p> |
| − | <p class="subtitle is- | + | <p class="subtitle is-5">Prof. Dr. Hasan Dağ, Kadir Has University</p> |
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| − | <div class="column is- | + | <div class="is-divider" data-content="Introduction"></div> |
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| + | <p>Data science expresses that previous data processing applications are not sufficient to process larger and more complex data sets. The relatively recent concepts of data mining, machine learning, and deep learning offer a new set of techniques and methods. Today, researchers and companies are dealing with and experimenting with various methods of deriving value, such as machine learning, data mining, artificial intelligence, and deep learning. Data Mining and Machine / Deep Learning track aims to contribute to fields that are related to analytics of data that based on different data types. New approaches, applications, models or methods related to the topic of this track.</p> | ||
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| − | + | <div class="is-divider" data-content="Biography of the Chair"></div> | |
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| − | + | <p>Prof. Dr. Hasan Dağ obtained his bachelor degree in electrical engineering from Istanbul Technical University, Istanbul, Turkey and obtained both his master and PhD degrees both in University of Wisconsin-Madison in electrical and Computer Engineering. His area of interest in general is computational science, data science and smart grid. His recent research areas are Data Science, Big Data, Cyber Security, and their application to Smart Grid. He holds the directorate position of research resources, while at the same time holding the position of the head of Management Information System at Kadir Has University, Istanbul, Turkey. He has also been appointed the directorate position of Research Center for Cyber Security and Critical Infrastructures.</p> | |
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| − | + | <div class="is-divider" data-content="Papers"></div> | |
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| − | <p class=" | + | <p class="is-small has-text-grey">Unsorted</p> |
| − | <p>< | + | <!-- 17 --> |
| − | <p> | + | <p><span class="icon" style="color: #e0470d;"><i class="fa fa-file-text-o"></i></span> Evaluation of Call Center Efficiency Using Text Mining Approach</p> |
| − | <p><span class="icon"><i class="fa fa- | + | <p class="is-small">Eda Üzüm, Boğaziçi University<br>Seren Başaran, Boğaziçi University<br>Sona Mardikyan, Boğaziçi University</p> |
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| − | <p class=" | + | <p><span class="icon" style="color: #e0470d;"><i class="fa fa-file-text-o"></i></span> Veri Madenciliği Üzerine Endüstriyel Bir Durum Çalışması</p> |
| − | <p>< | + | <p class="is-small">Buse Türkoğlu, Norm Civata<br>Murat Komesli, Yaşar University<br>Mehmet Süleyman Ünlütürk, Yaşar University</p> |
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| − | + | <p><span class="icon" style="color: #e0470d;"><i class="fa fa-file-text-o"></i></span> Balıkçılık Endüstrisinde Kullanılan Büyüme Modellerinde Geleneksel Yaklaşımlar ile Yapay Sinir Ağlarının Yaklaşımlarının Karşılaştırılması</p> | |
| − | + | <p class="is-small">Recep Benzer, National Defense University<br>Semra Benzer, Gazi University</p> | |
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| − | + | <p><span class="icon" style="color: #e0470d;"><i class="fa fa-file-text-o"></i></span> Integration of the Google Analytics tool into the data pre-processing layer for WEB Usage Mining: A case study</p> | |
| − | <!-- | + | <p class="is-small">Şükrü Can Şayan, Gazi University<br>Tahsin Çetinyokuş, Gazi University</p> |
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| − | + | <p><span class="icon" style="color: #e0470d;"><i class="fa fa-file-text-o"></i></span> Siğil Tedavisinde Kullanılan Immunotherapy Yönteminin Uygunluğunun Bayes Yöntemi ile Tespiti</p> | |
| − | + | <p class="is-small">Sümeyye Çelik, Burdur Mehmet Akif Ersoy University<br>Melike Şişeci Çeşmeli, Burdur Mehmet Akif Ersoy University<br>İhsan Pençe, Burdur Mehmet Akif Ersoy University<br>Adnan Kalkan, Burdur Mehmet Akif Ersoy University</p> | |
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| − | <p class=" | + | <p><span class="icon" style="color: #e0470d;"><i class="fa fa-file-text-o"></i></span> Predicting Diffusion Reach Probabilities via Representation Learning on Social Networks</p> |
| − | <p> | + | <p class="is-small">Furkan Gürsoy, Boğaziçi University<br>Ahmet Onur Durahim, Boğaziçi University</p> |
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| − | + | <p><span class="icon" style="color: #e0470d;"><i class="fa fa-file-text-o"></i></span> Finding a Model that Provides High Profits with Web Usage Mining: A Case Study</p> | |
| − | + | <p class="is-small">Şükrü Can Şayan, Gazi University<br>Tahsin Çetinyokuş, Gazi University</p> | |
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| − | + | <p><span class="icon" style="color: #e0470d;"><i class="fa fa-file-text-o"></i></span> Derin Öğrenme ile Görüntü Kümeleme</p> | |
| − | + | <p class="is-small">Ömer Faruk Akmeşe, Hitit University</p> | |
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| − | + | <p><span class="icon" style="color: #e0470d;"><i class="fa fa-file-text-o"></i></span> K-Means vs. Fuzzy C-Means: A Comparative Analysis of Two Popular Clustering Techniques on the Featured Mobile Applications Benchmark</p> | |
| − | + | <p class="is-small">Tuğrul Cabir Hakyemez, Sakarya University<br>Aysun Bozanta, Boğaziçi University<br>Mustafa Coşkun, Boğaziçi University</p> | |
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| − | + | <p><span class="icon" style="color: #e0470d;"><i class="fa fa-file-text-o"></i></span> A New Approach to Development of Recommendation Systems with Opinion Mining on Turkish User Reviews</p> | |
| − | + | <p class="is-small">Tayfun Yalçınkaya, Kadir Has University<br>Hasan Dağ, Kadir Has University</p> | |
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Track Data Mining and Machine/Deep Learning Track Chair Prof. Dr. Hasan Dağ, Kadir Has University Data science expresses that previous data processing applications are not sufficient to process larger and more complex data sets. The relatively recent concepts of data mining, machine learning, and deep learning offer a new set of techniques and methods. Today, researchers and companies are dealing with and experimenting with various methods of deriving value, such as machine learning, data mining, artificial intelligence, and deep learning. Data Mining and Machine / Deep Learning track aims to contribute to fields that are related to analytics of data that based on different data types. New approaches, applications, models or methods related to the topic of this track. Prof. Dr. Hasan Dağ obtained his bachelor degree in electrical engineering from Istanbul Technical University, Istanbul, Turkey and obtained both his master and PhD degrees both in University of Wisconsin-Madison in electrical and Computer Engineering. His area of interest in general is computational science, data science and smart grid. His recent research areas are Data Science, Big Data, Cyber Security, and their application to Smart Grid. He holds the directorate position of research resources, while at the same time holding the position of the head of Management Information System at Kadir Has University, Istanbul, Turkey. He has also been appointed the directorate position of Research Center for Cyber Security and Critical Infrastructures. Unsorted Evaluation of Call Center Efficiency Using Text Mining Approach Eda Üzüm, Boğaziçi University Veri Madenciliği Üzerine Endüstriyel Bir Durum Çalışması Buse Türkoğlu, Norm Civata Balıkçılık Endüstrisinde Kullanılan Büyüme Modellerinde Geleneksel Yaklaşımlar ile Yapay Sinir Ağlarının Yaklaşımlarının Karşılaştırılması Recep Benzer, National Defense University Integration of the Google Analytics tool into the data pre-processing layer for WEB Usage Mining: A case study Şükrü Can Şayan, Gazi University Siğil Tedavisinde Kullanılan Immunotherapy Yönteminin Uygunluğunun Bayes Yöntemi ile Tespiti Sümeyye Çelik, Burdur Mehmet Akif Ersoy University Predicting Diffusion Reach Probabilities via Representation Learning on Social Networks Furkan Gürsoy, Boğaziçi University Finding a Model that Provides High Profits with Web Usage Mining: A Case Study Şükrü Can Şayan, Gazi University Derin Öğrenme ile Görüntü Kümeleme Ömer Faruk Akmeşe, Hitit University K-Means vs. Fuzzy C-Means: A Comparative Analysis of Two Popular Clustering Techniques on the Featured Mobile Applications Benchmark Tuğrul Cabir Hakyemez, Sakarya University A New Approach to Development of Recommendation Systems with Opinion Mining on Turkish User Reviews Tayfun Yalçınkaya, Kadir Has University
Seren Başaran, Boğaziçi University
Sona Mardikyan, Boğaziçi University
Murat Komesli, Yaşar University
Mehmet Süleyman Ünlütürk, Yaşar University
Semra Benzer, Gazi University
Tahsin Çetinyokuş, Gazi University
Melike Şişeci Çeşmeli, Burdur Mehmet Akif Ersoy University
İhsan Pençe, Burdur Mehmet Akif Ersoy University
Adnan Kalkan, Burdur Mehmet Akif Ersoy University
Ahmet Onur Durahim, Boğaziçi University
Tahsin Çetinyokuş, Gazi University
Aysun Bozanta, Boğaziçi University
Mustafa Coşkun, Boğaziçi University
Hasan Dağ, Kadir Has University