Murat Can Ganiz

Contact Info:

Courses:

List of courses I am currently teaching or have taught recently. For a complete list please click here

• Fall 2022
  • CSE7052: Natural Language Processing , Thu 09:30-12:20 @M2-11, Office Hour: Tue 11:30
  • CSE3063: Object-oriented Software Design , Mon 09:30-11:20 @M1-Z01, Tue 09:30-10:20 @M2-Z11 Office Hours: Mon 11:30, Tue 10:30
• Spring 2022
  • CSE4062: Introduction to Data Science and Analytics
  • CSE4095: Introduction to Natural Language Processing
  • CSE2025: Data Structures

Research:

I am interested in Artificial Intelligence (AI) in general. More specifically Machine Learning algorithms applied to Natural Language Processing (NLP) and downstream NLP tasks such as text classification, sentiment analysis and Named Entity Recognition (NER). I am also interested and working on applying AI, in other word machine learning and deep learning to real world problems, working on structured or unstructured data, applying data science or data mining processes. Other topics of interest include graph mining, social network analysis and big data analytics.

Currently, I am managing Big Data and Text Analytics (BIGDaTA) Research Lab. in Marmara university, Computer Engineering Department.

Previously, I was managing Social Network Analysis and Data Mining (SoNADaM) Research Lab. (Doğuş University)

Projects:

• TÜBİTAK 1001 Scientific and Technological Research Projects Funding Program
  EEEAG, 116E239, 2017 - 2020, 30 Months, Principal Investigator
• TÜBİTAK 3501 Career Programme (National Young Researchers Career Development Programme)
  EEEAG, 111E239, 2012 - 2015, Principal Investigator
• TÜBİTAK TEYDEB 1512 Entrepreneurship Support, 2013, Entrepreneur (Sentiment Analysis and Opinion Mining, Social Network Analysis, Text Mining, Big Data Analytics).
• TÜBİTAK TEYDEB 1507 / 1501 / 1509 SME Funding Programme, 2012-2022, served or still serving as Scientific Advisor on several projects related to AI, Machine Learning, NLP, Deep Learning, and Recommendation Engines.

Publications & Patents:

• Akça, O, Bayrak, G., Issifu, A. M., Ganіz, M. C. (2022). Traditional Machine Learning and Deep Learning-based Text Classification for Turkish Law Documents using Transformers and Domain Adaptation. In 2022 International Conference on INnovations in Intelligent SysTems and Applications (INISTA), 2022, pp. 1-6, doi: 10.1109/INISTA55318.2022.9894051.


• Çelіkmasat, G., Aktürk, M. E., Ertunç, Y. E., Issifu, A. M., Ganіz, M. C. (2022). Biomedical Named Entity Recognition Using Transformers with biLSTM+ CRF and Graph Convolutional Neural Networks. In 2022 International Conference on INnovations in Intelligent SysTems and Applications (INISTA) (pp. 1-6). IEEE.


• Bayrak, G., Toprak, M. Ş., Ganiz, M. C., Kodaz, H., & Koç, U. (2022). Deep Learning-Based Brain Hemorrhage Detection in CT Reports. In Challenges of Trustable AI and Added-Value on Health (pp. 866-867). IOS Press. (In Medical Informatics Europe 2022 Conference)


• Sarıyer, M., Akıl, A., Bulgurcu, F. N., Öge, F. E., & Ganiz, M. C. (2022). Individual Stock Price Prediction by Using KAP and Twitter Sentiments with Machine Learning for BIST30. In 2022 International Conference on INnovations in Intelligent SysTems and Applications (INISTA) (pp. 1-6). IEEE.


• Issifu, A. M., & Ganiz, M. C. (2021). A Simple Data Augmentation Method to Improve the Performance of Named Entity Recognition Models in Medical Domain. In 2021 6th International Conference on Computer Science and Engineering (UBMK) (pp. 763-768). IEEE.


• Abbasli, N., & Ganiz, M. C. (2021). Log and Execution Trace Analytics System. In 2021 International Conference on INnovations in Intelligent SysTems and Applications (INISTA) (pp. 1-7). IEEE.


• Ugur, O., Arisoy, A. A., Ganiz, M. C., & Bolac, B. (2021). Descriptive and Prescriptive Analysis of Construction Site Incidents Using Decision Tree Classification and Association Rule Mining. In 2021 International Conference on INnovations in Intelligent SysTems and Applications (INISTA) (pp. 1-6). IEEE.


• Altinel, A. B., Hakkoz, M. A., Bozdag, E. B., & Ganiz, M.C. (2020). Identifying Topic-based Opinion Leaders in Social Networks by Content and User Information. International Journal of Intelligent Systems and Applications in Engineering, 8(4), 214-220.


• Altınel, A. B., Ganiz, M. C., Şipal, B., Erkaya, E. C., Yücedağ, O. C., & Doğan, M. A. (2019). Word sense disambiguation using semantic kernels with class-based term values. Turkish Journal of Electrical Engineering & Computer Sciences, 27(4), 3180-3194.


• Değirmenci, S., Gerek, A., Ganiz, M.C. (2019). Waste Not: Meta-Embedding of Word and Context Vectors . 24th International Conference on Applications of Natural Language to Information Systems (NLDB 2019), 26–28 June 2019, University of Salford, MediaCityUK Campus, United Kingdom


• Gerek, A., Yüney, M.C., Erkaya, E., Ganiz, M.C. (2019). Effects of Positivization on the Paragraph Vector Model. International Symposium on INnovations in Intelligent SysTems and Applications (INISTA 2019), Sofia, Bulgaria, July 3-5, 2019


• Kocaman, G., Şipal, B., Gerek, A., Altınel, B., Ganiz, M.C. (2019). Diffused Label Propagation based Transductive Classification Algorithm for Word Sense Disambiguation. International Symposium on INnovations in Intelligent SysTems and Applications (INISTA 2019), Sofia, Bulgaria, July 3-5, 2019


• Şen, M. U., Erdinç, H. Y., Yavuzalp, B., Ganiz, M. C. (2019). Combining Lexical and Semantic Similarity Methods for News Article Matching. 2nd International Data Science Conference (iDSC 2019), May 22nd - 24th 2019, Salzburg, Austria


• Kalaycı, T. A., Asan, U., Ganiz, M.C., & Gerek, A. (2019). A New Cluster-Aware Regularization of Neural Networks. In International Conference on Intelligent and Fuzzy Systems (INFUS 2019) (pp. 346-353). Springer, Cham.


• Altınel, B., & Ganiz, M.C. (2018). Semantic text classification: A survey of past and recent advances. Information Processing & Management, 54(6), 1129-1153.


• Çelenli, H. İ., Öztürk, S. T., Şahin, G., Gerek, A., & Ganiz, M.C. (2018). Document Embedding Based Supervised Methods for Turkish Text Classification. In 2018 3rd International Conference on Computer Science and Engineering (UBMK) (pp. 477-482). IEEE.


• Altınel, B., Ganiz, M. C., & Diri, B. (2017). Instance labeling in semi-supervised learning with meaning values of words. Engineering Applications of Artificial Intelligence , 62, 152-163.


• Taşpınar, M., Ganiz, M. C., & Acarman, T. (2017). A Feature Based Simple Machine Learning Approach with Word Embeddings to Named Entity Recognition on Tweets. 22nd International Conference on Natural Language & Information Systems (NLDB'2017), Liège, Belgium, June 21-23, 2017 (pp. 254-259). Springer, Cham.


• Kantepe, M., & Ganiz, M. C. (2017). Preprocessing framework for Twitter bot detection. In proceedings of 2017 International Conference on Computer Science and Engineering (UBMK), Antalya, Turkey, (pp. 630-634).


• Karakurt, İ., Özer, S., Ulusinan, T., & Ganiz, M. C. (2017). A machine learning approach to database failure prediction. In proceedings of 2017 International Conference on Computer Science and Engineering (UBMK), Antalya, Turkey, (pp. 1030-1035).


• Çamurdan, Z., & Ganiz, M. C. (2017). Machine learning based electricity demand forecasting. In proceedings of 2017 International Conference on Computer Science and Engineering (UBMK), Antalya, Turkey, (pp. 412-417).


• Ganiz, M. C. (2016). Semi-supervised learning using higher-order co-occurrence paths to overcome the complexity of data representation. 2016 IEEE International Conference on Systems, Man, and Cybernetics (IEEE SMC 2016), October 9-12, Budapest, Hungary (pp. 002242-002247).


• Altınel, B., Ganiz, M.C. (2016). A new hybrid semi-supervised algorithm for text classification with class-based semantics. Knowledge-Based Systems (New Avenues in Knowledge Bases for Natural Language Processing) ,DOI:10.1016/j.knosys.2016.06.021, Volume 108, 15 September 2016, Pages 50–64


• Tutkan, M., Ganiz, M.C., Akyokuş, S. (2016). Helmholtz Principle based Supervised and Unsupervised Feature Selection Methods for Text Mining. Information Processing & Management ,DOI:10.1016/j.ipm.2016.03.007, Volume 52, Issue 5, September 2016, Pages 885–910


• Altınel, B., Diri, B., Ganiz, M.C. (2015). A Novel Semantic Smoothing Kernel for Text Classification with Class-based Weighting. Knowledge-Based Systems ,Vol. 89, pp. 265-177


• Altınel, B., Ganiz, M.C., Diri, B., (2015). A Corpus-Based Semantic Kernel for Text Classification by Using Meaning Values of Terms. Engineering Applications of Artificial Intelligence , Vol. 43, pp. 54-66


• Ganiz, M.C., Tutkan, M., Akyokuş, S. (2015). A Novel Classifier Based on Meaning for Text Classification. Innovations in Intelligent Systems and Applications (INISTA 2015) , September 2-4, Madrid, Spain.


• Kilimci, Z.H., Ganiz, M.C. (2015). Evaluation of Classification Models for Language Processing. Innovations in Intelligent Systems and Applications (INISTA 2015) , September 2-4, Madrid, Spain.


• Turan, M., Sönmez, C., Ganiz, M.C. (2014). The Benchmark of Paragraph and Sentence Extraction Summaries on Outlier Document Filtering Applied Multi-Document Summarizer. Information Technology And Control ,Vol.43，No.4, 2014, pp.433-439


• Tutkan, M., Ganiz, M.C., Akyokuş, S.(2014). Metin Sınıflandırma için Eğitimsiz bir Anlamsal Özellik Seçimi Yöntemi (An Unsupervised Semantic Attribute Selection Method for Text Classification). Elektrik – Elektronik – Bilgisayar ve Biyomedikal Mühendisliği Sempozyumu (ELECO 2014), ,27 – 29 Kasım 2014, Bursa, Türkiye.


• Tutkan, M., Ganiz, M.C., Akyokuş, S.(2014). Metin Sınıflandırma için Yeni Bir Eğitimli Anlamsal Özellik Seçimi Yöntemi. Akıllı Sistemlerde Yenilikler ve Uygulamalar Sempozyumu (ASYU 2014) , Ekim 9-10, İzmir Katip Çelebi Üniversitesi, İzmir, Türkiye.


• Poyraz, M., Kilimci, Z.H., Ganiz, M.C. (2014). Higher-Order Smoothing: A Novel Semantic Smoothing Method for Text Classification. Journal Of Computer Science and Technology , Vol.29，No.3, 2014, pp.376-391
  (Please email me for the Turkish and English Textual Datasets used in this study)


• Altınel, B., Ganiz, M.C., Diri, B., (2014). A Simple Semantic Kernel Approach for SVM using Higher-Order Paths. Innovations in Intelligent Systems and Applications (INISTA 2014) , June 23-25, Alberobello, Italy.


• Altınel, B., Ganiz, M.C., Diri, B., (2014). A Semantic Kernel for Text Classification Based on Iterative-Higher–Order Relations between Words and Documents. The 13th International Conference on Artificial Intelligence and Soft Computing (ICAISC 2014) , June 1-5, Zakopane, Poland.


• Altınel, B., Ganiz, M.C., Diri, B., (2013). A Novel Higher-order Semantic Kernel. The 10th International Conference on Electronics Computer and Computation (ICECCO 2013) , November 7-9, Ankara, Turkey.
  (Selected 'Best Track Paper', Machine Learning and Computational Intelligence Track)


• Torunoğlu, D., Telseren, G., Sağtürk, Ö.,Ganiz, M.C. (2013). Wikipedia Based Semantic Smoothing for Twitter Sentiment Classification. Innovations in Intelligent Systems and Applications (INISTA 2013), June 19-21, Albena, Bulgaria.


• Poyraz, M., Kilimci, Z.H., Ganiz, M.C.(2012). A Novel Semantic Smoothing Method based on Higher Order Paths for Text Classification . IEEE International Conference on Data Mining (ICDM 2012) , December 10-13, 2012, Brussels, Belgium


• Uykan, Z., Ganiz, M.C., Sahinli, C. (2012). Discrete-Time Hopfield Neural Network Based Text Clustering Algorithm. 19th International Conference on Neural Information Processing (ICONIP 2012) , November 12-15, 2012, Doha, Qatar.


• Poyraz, M., Ganiz, M.C., Akyokus, S., Gorener, B., Kilimci, Z.H. (2012). Exploiting Turkish Wikipedia as a Semantic Resource for Text Classification. Innovations in Intelligent Systems and Applications (INISTA 2012), July 2-4, 2012, Trabzon, Turkiye.


• Ganiz, M., George, C., Pottenger, W.M. (2011). Higher Order Naïve Bayes: A Novel Non-IID Approach to Text Classification. IEEE Transactions on Knowledge and Data Engineering, vol. 23, no. 7, pp. 1022-1034, July 2011.


• Uykan, Z., Ganiz, M.C. (2011). Application of the SpecHybrid Algorithm to Text Document Clustering Problem. Innovations in Intelligent Systems and Applications (INISTA 2011), June, 2011, Istanbul, Turkiye.


• Torunoğlu, D., Çakırman, E., Ganiz, M.C., Akyokuş, S., Gürbüz, M.Z. (2011). Analysis of Preprocessing Methods on Classification of Turkish Texts. Innovations in Intelligent Systems and Applications (INISTA 2011) , June, 2011, Istanbul, Turkiye.


• Cazenave, I.O.U, Köşlük, E., Ganiz, M.C. (2011). An Anomaly Detection Framework for BGP. Innovations in Intelligent Systems and Applications (INISTA 2011), June, 2011, Istanbul, Turkiye.


• William M Pottenger, Nikita Lytkin, Murat C Ganiz (2010). Systems and Methods for Data Transformation Using Higher Order Learning. US Patent App. 12/797,366, 2010.


• Ganiz, M., Lytkin, N. , Pottenger, W.M. (2009). Leveraging Higher Order Dependencies between Features for Text Classification. In Proceedings of ECML/PKDD Conference, September, 2009, Bled, Slovenia.


• Ganiz, M., Pottenger, W.M., Kanitkar, S., Chuah, M.C. (2006). Detection of Interdomain Routing Anomalies Based on Higher-Order Path Analysis. In Proceedings of the Sixth IEEE International Conference on Data Mining (ICDM 2006), December 2006, Hong Kong, China


• Li, S., Janneck, C.D., Belapurkar, A.P., Ganiz, M.C., Yang, X., Dilsizian, M., Wu, T., Bright, J.M., Pottenger, W.M. (2007). Mining Higher-Order Association Rules from Distributed Named Entity Databases. In Proceedings of IEEE International Conference on Intelligence and Security Informatics (ISI’07), May 2007, New Brunswick, NJ, U.S.A


• Ganiz, M., Pottenger, W.M. and Yang, X. (2006). Link Analysis of Higher-Order Paths in Supervised Learning Datasets . In Proceedings of the Workshop on Link Analysis, Counterterrorism and Security, 2006 SIAM Conference on Data Mining, Bethesda, MD, April.


• Li, S., Janneck, C.D., Pottenger, W.M., Belapurkar, A.P., Ganiz, M., Wu, T. (2006). Mining Higher-Order Association Rules from Distributed Named Entity Databases . Lehigh University, CSE Department, Technical Report, LU-CSE-06-005


• Ganiz, M., Pottenger, W.M., Janneck, C.D. (2005). Recent Advances in Literature Based Discovery . Lehigh University, CSE Department, Technical Report, LU-CSE-05-027

Education:

• Ph.D. in Computer Science, Lehigh University , PA, U.S.A, 2008.
• B.S. and M.S. in Computer Engineering, Selcuk University, 2000 and 2002.

Memberships:

The list may not be up to date...
• IEEE - Institute of Electrical and Electronics Engineers
• Computer Society, IEEE
• Big Data Community, IEEE
• Cloud Computing Community, IEEE

Personal:

"Without knowing the force of words, it is impossible to know men" -- Confucius

"Truth is stranger than fiction, but it is because Fiction is obliged to stick possibilities; Truth isn't." -- Mark Twain