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Tevfik Aytekin
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2020 – today
- 2024
- [i1]Mert Burabak, Tevfik Aytekin:
SynerGraph: An Integrated Graph Convolution Network for Multimodal Recommendation. CoRR abs/2405.19031 (2024) - 2022
- [j9]Osman Semih Albayrak
, Tevfik Aytekin
, Tolga Ahmet Kalayci
:
Duplicate product record detection engine for e-commerce platforms. Expert Syst. Appl. 193: 116420 (2022) - 2021
- [j8]Ethem Çanakoglu
, Ibrahim Muter
, Tevfik Aytekin
:
Integrating Individual and Aggregate Diversity in Top-N Recommendation. INFORMS J. Comput. 33(1): 300-318 (2021) - 2020
- [j7]A. Murat Yagci
, Tevfik Aytekin
, Fikret S. Gürgen:
A Meta-Algorithm for Improving Top-N Prediction Efficiency of Matrix Factorization Models in Collaborative Filtering. Int. J. Pattern Recognit. Artif. Intell. 34(3): 2059007:1-2059007:20 (2020)
2010 – 2019
- 2019
- [j6]A. Murat Yagci
, Tevfik Aytekin
, Fikret S. Gürgen:
Parallel pairwise learning to rank for collaborative filtering. Concurr. Comput. Pract. Exp. 31(15) (2019) - [j5]Ahmet Maruf Aytekin
, Tevfik Aytekin
:
Real-time recommendation with locality sensitive hashing. J. Intell. Inf. Syst. 53(1): 1-26 (2019) - [c11]Abdullah Uslu, Sefa Tekin, Tevfik Aytekin
:
SENTIMENT ANALYSIS IN TURKISH FILM COMMENTS. SIU 2019: 1-4 - [c10]Tugba Zeynep Yildiz, Tevfik Aytekin
:
Short term water demand forecasting using regional data. SIU 2019: 1-4 - 2018
- [j4]Mahmut Özge Karakaya, Tevfik Aytekin
:
Effective methods for increasing aggregate diversity in recommender systems. Knowl. Inf. Syst. 56(2): 355-372 (2018) - 2017
- [j3]A. Murat Yagci
, Tevfik Aytekin
, Fikret S. Gürgen:
Scalable and adaptive collaborative filtering by mining frequent item co-occurrences in a user feedback stream. Eng. Appl. Artif. Intell. 58: 171-184 (2017) - [j2]Ibrahim Muter, Tevfik Aytekin
:
Incorporating Aggregate Diversity in Recommender Systems Using Scalable Optimization Approaches. INFORMS J. Comput. 29(3): 405-421 (2017) - [c9]A. Murat Yagci
, Tevfik Aytekin
, Fikret S. Gürgen:
On Parallelizing SGD for Pairwise Learning to Rank in Collaborative Filtering Recommender Systems. RecSys 2017: 37-41 - 2016
- [c8]Muhammed Macit
, Emrullah Delibas, Bahtiyar Karanlik, Alperen Inal, Tevfik Aytekin
:
Real time distributed analysis of MPLS network logs for anomaly detection. NOMS 2016: 750-753 - [c7]A. Murat Yagci
, Tevfik Aytekin
, Fikret S. Gürgen:
Balanced random forest for imbalanced data streams. SIU 2016: 1065-1068 - 2015
- [c6]A. Murat Yagci
, Tevfik Aytekin
, Fikret S. Gürgen:
An ensemble approach for multi-label classification of item click sequences. RecSys Challenge 2015: 7:1-7:4 - [c5]Ahmet Maruf Aytekin, Tevfik Aytekin
:
Locality sensitive hashing based scalable collaborative filtering. SIU 2015: 1030-1033 - 2014
- [j1]Tevfik Aytekin
, Mahmut Özge Karakaya:
Clustering-based diversity improvement in top-N recommendation. J. Intell. Inf. Syst. 42(1): 1-18 (2014) - 2013
- [c4]Ceyhun Can Ülker, Tevfik Aytekin
:
Improving the performance of active voxel selection in the analysis of fMRI data using genetic algorithms. BCI 2013: 129-136 - 2012
- [c3]Olcay Kursun
, Tevfik Aytekin
:
Combining Spatial Proximity and Temporal Continuity for Learning Invariant Representations. ASONAM 2012: 871-873 - [c2]Osman Baskaya, Tevfik Aytekin:
How Similar is Rating Similarity to Content Similarity? RUE@RecSys 2012: 27-29
1990 – 1999
- 1994
- [c1]Tevfik Aytekin
, Emin Erkan Korkmaz
, H. Altay Güvenir
:
An Application of Genetic Programming to the 4-Op Problem Using Map-Trees. Evo Workshops 1994: 28-40
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