Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies
if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the
same subfield and year (this is the minimum needed to enter the top 1%, not the average
within it), or reaches the top citation threshold in at least one of its specific research
topics.
State-of-the-art in privacy preserving data mining
2004523 citationsVassilios S. Verykios, Yücel Saygın et al.profile →
Peers — A (Enhanced Table)
Peers by citation overlap · career bar shows stage (early→late)
cites ·
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This map shows the geographic impact of Yücel Saygın's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Yücel Saygın with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yücel Saygın more than expected).
This network shows the impact of papers produced by Yücel Saygın. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Yücel Saygın. The network helps show where Yücel Saygın may publish in the future.
Co-authorship network of co-authors of Yücel Saygın
This figure shows the co-authorship network connecting the top 25 collaborators of Yücel Saygın.
A scholar is included among the top collaborators of Yücel Saygın based on the total number of
citations received by their joint publications. Widths of edges
represent the number of papers authors have co-authored together.
Node borders
signify the number of papers an author published with Yücel Saygın. Yücel Saygın is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Saygın, Yücel, et al.. (2020). Discovering the prerequisite relationships among instructional videos from subtitles. Sabanci University.2 indexed citations
İnan, Ali, Mehmet Ercan Nergiz, & Yücel Saygın. (2017). Student Data Protection: A Technical Assessment in the Context of the Fatih Project. Bilişim Teknolojileri Dergisi. 10(1). 67–77.
6.
Yanıkoğlu, Berrin, et al.. (2013). SU-Sentilab : A Classification System for Sentiment Analysis in Twitter. Scuola Normale Superiore di Pisa. 2. 471–477.12 indexed citations
7.
Yanıkoğlu, Berrin, et al.. (2012). New features for sentiment analysis: Do sentences matter?. Sabanci University. 5–15.13 indexed citations
8.
Tamersoy, Acar, Grigorios Loukides, Mehmet Ercan Nergiz, Yücel Saygın, & Bradley Malin. (2012). Anonymization of Longitudinal Electronic Medical Records. IEEE Transactions on Information Technology in Biomedicine. 16(3). 413–423.49 indexed citations
Saygın, Yücel & Maria Luisa Damiani. (2011). Foreword for the special issue of selected papers from the 3rd ACM SIGSPATIAL Workshop on Security and Privacy in GIS and LBS. 4(2). 51–53.
Dimitrakakis, Christos, et al.. (2010). Proceedings of the international ECML/PKDD conference on Privacy and security issues in data mining and machine learning.1 indexed citations
15.
Çobanoğlu, Murat Can, Yücel Saygın, & Osman Uğur Sezerman. (2010). Classification of GPCRs Using Family Specific Motifs. IEEE/ACM Transactions on Computational Biology and Bioinformatics. 8(6). 1495–1508.15 indexed citations
16.
Nergiz, Mehmet Ercan, et al.. (2009). Towards Trajectory Anonymization: a Generalization-Based Approach. Sabanci University. 2(1). 47–75.98 indexed citations
Bonchi, Francesco, Elena Ferrari, Bradley Malin, & Yücel Saygın. (2007). Proceedings of the 1st ACM SIGKDD international conference on Privacy, security, and trust in KDD. Knowledge Discovery and Data Mining.2 indexed citations
19.
Lévi, Albert, Erkay Savaş, Hüsnü Yenigün, Selim Balcısoy, & Yücel Saygın. (2007). Computer and Information Sciences - ISCIS 2006: 21th International Symposium Istanbul, Turkey, Novenber 1-3, 2006, Proceedings (Lecture Notes in Computer Science). Springer eBooks.
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive
bibliographic database. While OpenAlex provides broad and valuable coverage of the global
research landscape, it—like all bibliographic datasets—has inherent limitations. These include
incomplete records, variations in author disambiguation, differences in journal indexing, and
delays in data updates. As a result, some metrics and network relationships displayed in
Rankless may not fully capture the entirety of a scholar's output or impact.