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İhsan Güneş

ResearcherPublications, citations & collaboration network

İhsan Güneş is a researcher indexed in ScholarIQ from OpenAlex & ORCID. ScholarIQ records 38 works, 553 citations, an h-index of 9 and an i10-index of 9.

38
Works
553
Citations
9
h-index
9
i10-index

How has İhsan Güneş's publication output changed over time?

ScholarIQpublication output · 2010–2024

Output grew0% over the shown period — from 1 works in 2010 to 1 in 2024.

1
1
4
1
1
1
1
1
20102012201320162019202020232024

What are the most-cited papers on İhsan Güneş?

ScholarIQmost cited works
Shilling attacks against recommender systems: a comprehensive survey
İhsan Güneş, Cihan Kaleli, Alper Bilge, Hüseyin Polat
Artificial Intelligence Review. 2012329 Citations
A SURVEY OF PRIVACY-PRESERVING COLLABORATIVE FILTERING SCHEMES
Alper Bilge, Cihan Kaleli, İbrahim Yakut, İhsan Güneş, Hüseyin Polat
International Journal of Software Engineering and Knowledge Engineering. 201343 Citations
Artificial intelligence system for automatic maxillary sinus segmentation on cone beam computed tomography images
İbrahim Şevki Bayrakdar, Nermin Sameh Elfayome, Reham Ashraf Hussien, İbrahim Tevfik Gülşen, Alican Kuran, İhsan Güneş, A. A. Al-badr, Özer Çelik, Kaan Orhan
S32481061. 202434 CitationsOPEN ACCESS
Shilling Attacks Against Memory-Based Privacy-Preserving Recommendation Algorithms
İhsan Güneş, Alper Bilge, Hüseyin Polat
S204131793. 201333 CitationsOPEN ACCESS
Robustness analysis of privacy-preserving model-based recommendation schemes
Alper Bilge, İhsan Güneş, Hüseyin Polat
Expert Systems with Applications. 201326 Citations

Related on ScholarIQ

Eskisehir Technical University
Institution
Shilling attacks against recommender systems: a comprehensive survey
Paper
A SURVEY OF PRIVACY-PRESERVING COLLABORATIVE FILTERING SCHEMES
Paper
Artificial intelligence system for automatic maxillary sinus segmentation on cone beam computed tomography images
Paper
Shilling Attacks Against Memory-Based Privacy-Preserving Recommendation Algorithms
Paper
Robustness analysis of privacy-preserving model-based recommendation schemes
Paper
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