A Join-Less Approach for Co-Location Pattern Mining: A Summary of Results. - Jin Soung Yoo; Shashi Shekhar 001; Mete Celik (ICDM, 2005)

Mixed-Drove Spatio-Temporal Co-occurence Pattern Mining: A Summary of Results. - Mete Celik; Shashi Shekhar 001; James P. Rogers; James A. Shine; Jin Soung Yoo (ICDM, 2006)

Sustained Emerging Spatio-Temporal Co-occurrence Pattern Mining: A Summary of Results. - Mete Celik; Shashi Shekhar 001; James P. Rogers; James A. Shine (ICTAI, 2006)

Discovery of Co-evoluting Spatial Co-located Event Sets. - Jin Soung Yoo; Shashi Shekhar 001; Sangho Kim 001; Mete Celik (SDM, 2006)

Mining At Most Top-K% Mixed-drove Spatio-temporal Co-occurrence Patterns: A Summary of Results. - Mete Celik; Shashi Shekhar 001; James P. Rogers; James A. Shine; James M. Kang (ICDE Workshops, 2007)

Zonal Co-location Pattern Discovery with Dynamic Parameters. - Mete Celik; James M. Kang; Shashi Shekhar 001 (ICDM, 2007)

Spatial and Spatiotemporal Data Mining. - Shashi Shekhar 001; Ranga Raju Vatsavai; Mete Celik (Next Generation of Data Mining, 2008)

Should SDBMS support a join index?: a case study from CrimeStat. - Pradeep Mohan; Ronald E. Wilson; Shashi Shekhar 001; Betsy George; Ned Levine; Mete Celik (GIS, 2008)

Mixed-Drove Spatiotemporal Co-Occurrence Pattern Mining. - Mete Celik; Shashi Shekhar 001; James P. Rogers; James A. Shine (IEEE Trans. Knowl. Data Eng., 2008)

Spatial AutoRegression (SAR) Model - Parameter Estimation Techniques. - Baris M. Kazar; Mete Celik (Springer, 2012)

Performance analysis of ABCMiner algorithm with different objective functions. - Fehim Köylü; Mete Celik; Dervis Karaboga (SIU, 2013)

Partial spatio-temporal co-occurrence pattern mining. - Mete Celik (Knowl. Inf. Syst., 2015)

CoABCMiner: An Algorithm for Cooperative Rule Classification System Based on Artificial Bee Colony. - Mete Celik; Fehim Köylü; Dervis Karaboga (Int. J. Artif. Intell. Tools, 2016)

Discovering socially important locations of social media users. - Ahmet Sakir Dokuz; Mete Celik (Expert Syst. Appl., 2017)

Discovering socio-spatio-temporal important locations of social media users. - Mete Celik; Ahmet Sakir Dokuz (J. Comput. Sci., 2017)

Discovering socially similar users in social media datasets based on their socially important locations. - Mete Celik; Ahmet Sakir Dokuz (Inf. Process. Manag., 2018)

An Efficient Tree-Based Algorithm for Mining High Average-Utility Itemset. - Irfan Yildirim; Mete Celik (IEEE Access, 2019)

Developing structural profile matrices for protein secondary structure and solvent accessibility prediction. - Zafer Aydin; Nuh Azginoglu; Halil Ibrahim Bilgin; Mete Celik (Bioinform., 2019)

Cloud Computing-Based Socially Important Locations Discovery on Social Media Big Datasets. - Ahmet Sakir Dokuz; Mete Celik (Int. J. Inf. Technol. Decis. Mak., 2020)

RNN-GWR: A geographically weighted regression approach for frequently updated data. - Murat Tasyurek; Mete Celik (Neurocomputing, 2020)

Structural profile matrices for predicting structural properties of proteins. - Nuh Azginoglu; Zafer Aydin; Mete Celik (J. Bioinform. Comput. Biol., 2020)

Mining High-Average Utility Itemsets with Positive and Negative External Utilities. - Irfan Yildirim; Mete Celik (New Gener. Comput., 2020)

Hybrid models based on genetic algorithm and deep learning algorithms for nutritional Anemia disease classification. - Serhat Kiliçarslan; Mete Celik; Safak Sahin (Biomed. Signal Process. Control., 2021)

Convolutional neural network analysis of recurrence plots for high resolution melting classification. - Fatma Ozge Ozkok; Mete Celik (Comput. Methods Programs Biomed., 2021)

RSigELU: A nonlinear activation function for deep neural networks. - Serhat Kiliçarslan; Mete Celik (Expert Syst. Appl., 2021)

A Hybrid Validity Index to Determine K Parameter Value of k-Means Algorithm for Time Series Clustering. - Fatma Ozge Ozkok; Mete Celik (Int. J. Inf. Technol. Decis. Mak., 2021)

A hybrid CNN-LSTM model for high resolution melting curve classification. - Fatma Ozge Ozkok; Mete Celik (Biomed. Signal Process. Control., 2022)

KAF + RSigELU: a nonlinear and kernel-based activation function for deep neural networks. - Serhat Kiliçarslan; Mete Celik (Neural Comput. Appl., 2022)

4D-GWR: geographically, altitudinal, and temporally weighted regression. - Murat Tasyurek; Mete Celik (Neural Comput. Appl., 2022)

Parametric RSigELU: a new trainable activation function for deep learning. - Serhat Kiliçarslan; Mete Celik (Neural Comput. Appl., 2024)

Discovering and Ranking Urban Social Clusters Out of Streaming Social Media Datasets. - Mete Celik; Ahmet Sakir Dokuz; Alper Ecemis; Emre Erdogmus (Concurr. Comput. Pract. Exp., 2025)