Olfa Nasraoui

5.2k total citations
164 papers, 2.9k citations indexed

About

Olfa Nasraoui is a scholar working on Artificial Intelligence, Information Systems and Computer Vision and Pattern Recognition. According to data from OpenAlex, Olfa Nasraoui has authored 164 papers receiving a total of 2.9k indexed citations (citations by other indexed papers that have themselves been cited), including 84 papers in Artificial Intelligence, 78 papers in Information Systems and 37 papers in Computer Vision and Pattern Recognition. Recurrent topics in Olfa Nasraoui's work include Recommender Systems and Techniques (45 papers), Web Data Mining and Analysis (27 papers) and Data Mining Algorithms and Applications (24 papers). Olfa Nasraoui is often cited by papers focused on Recommender Systems and Techniques (45 papers), Web Data Mining and Analysis (27 papers) and Data Mining Algorithms and Applications (24 papers). Olfa Nasraoui collaborates with scholars based in United States, Colombia and Germany. Olfa Nasraoui's co-authors include Raghu Krishnapuram, Hichem Frigui, Zhiyong Zhang, Anupam Joshi, Leyla Zhuhadar, Behnoush Abdollahi, Fabio A. González, Ehsan Hosseini-Asl, Jacek M. Żurada and Patrick Shafto and has published in prestigious journals such as PLoS ONE, IEEE Access and Pattern Recognition.

In The Last Decade

Olfa Nasraoui

154 papers receiving 2.7k citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Olfa Nasraoui United States 27 1.6k 1.2k 737 503 326 164 2.9k
Αλέξανδρος Νανόπουλος Germany 26 1.3k 0.8× 1.2k 1.0× 711 1.0× 680 1.4× 395 1.2× 101 2.9k
Dan Pelleg United States 17 1.4k 0.9× 923 0.8× 572 0.8× 527 1.0× 446 1.4× 42 2.7k
D. Sculley United States 21 1.7k 1.1× 940 0.8× 641 0.9× 261 0.5× 453 1.4× 37 3.4k
Ralf Herbrich United Kingdom 28 2.1k 1.3× 791 0.7× 1.0k 1.4× 358 0.7× 258 0.8× 70 3.6k
Prem Melville United States 21 1.7k 1.1× 1.0k 0.9× 531 0.7× 166 0.3× 224 0.7× 40 2.7k
Gui-Rong Xue China 28 2.9k 1.8× 1.6k 1.4× 1.3k 1.8× 340 0.7× 378 1.2× 56 4.6k
Ge Yu China 30 1.6k 1.0× 721 0.6× 636 0.9× 641 1.3× 1.1k 3.3× 380 3.8k
Christopher Meek United States 31 2.3k 1.5× 996 0.8× 354 0.5× 670 1.3× 478 1.5× 81 3.5k
Xiaoyong Du China 29 1.9k 1.2× 1.1k 0.9× 692 0.9× 430 0.9× 824 2.5× 317 3.5k
Jaana Kekäläinen Finland 13 2.4k 1.5× 2.6k 2.2× 1.1k 1.4× 529 1.1× 389 1.2× 37 4.4k

Countries citing papers authored by Olfa Nasraoui

Since Specialization
Citations

This map shows the geographic impact of Olfa Nasraoui'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 Olfa Nasraoui with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Olfa Nasraoui more than expected).

Fields of papers citing papers by Olfa Nasraoui

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Olfa Nasraoui. 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 Olfa Nasraoui. The network helps show where Olfa Nasraoui may publish in the future.

Co-authorship network of co-authors of Olfa Nasraoui

This figure shows the co-authorship network connecting the top 25 collaborators of Olfa Nasraoui. A scholar is included among the top collaborators of Olfa Nasraoui 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 Olfa Nasraoui. Olfa Nasraoui is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Das, Sumit Kumar, et al.. (2025). Comparative Analysis of Post Hoc Explainable Methods for Robotic Grasp Failure Prediction. Electronics. 14(9). 1868–1868. 1 indexed citations
2.
Qaffas, Alaa A., et al.. (2023). An Explainable Artificial Intelligence Approach for Multi-Criteria ABC Item Classification. Journal of theoretical and applied electronic commerce research. 18(2). 848–866. 9 indexed citations
4.
Yang, Scott Cheng‐Hsin, et al.. (2017). Unifying recommendation and active learning for human-algorithm interactions.. Cognitive Science. 2 indexed citations
5.
Zhuhadar, Leyla, et al.. (2016). Computer-Assisted Learning Based on Universal Design, Multimodal Presentation and Textual Linkage. Journal of the Knowledge Economy. 7(2). 373–387. 4 indexed citations
6.
Nasraoui, Olfa, et al.. (2016). Analysis and visualization of a literature-mined glaucoma gene interaction network. 669–676. 2 indexed citations
7.
Hosseini-Asl, Ehsan, Jacek M. Żurada, & Olfa Nasraoui. (2015). Deep Learning of Part-Based Representation of Data Using Sparse Autoencoders With Nonnegativity Constraints. IEEE Transactions on Neural Networks and Learning Systems. 27(12). 2486–2498. 160 indexed citations
8.
Nasraoui, Olfa, et al.. (2014). From tweets to stories: using stream-dashboard to weave the twitter data stream into dynamic cluster models. 182–197. 2 indexed citations
9.
Yang, Rong, Leyla Zhuhadar, & Olfa Nasraoui. (2011). Bow-tie decomposition in directed graphs. International Conference on Information Fusion. 1–5. 8 indexed citations
10.
Nasraoui, Olfa, et al.. (2010). Robust Clustering of Data Streams using Incremental Optimization.. 5 indexed citations
11.
Zhuhadar, Leyla, et al.. (2009). How to Build an Ontology Driven Information Retrieval System.. 80–85. 2 indexed citations
13.
Zhuhadar, Leyla, et al.. (2009). Evaluating Multi-Model (Metadata-Semantic) Information Retrieval System.. International Conference on Artificial Intelligence. 125–130. 1 indexed citations
14.
Zhuhadar, Leyla, Olfa Nasraoui, & Róbert E. Wyatt. (2008). A Comparsion Study Between Generic and Metadata Search Engines in an E-learning Environment.. 500–505. 2 indexed citations
15.
Khribi, Mohamed Koutheaïr, Mohamed Jemni, & Olfa Nasraoui. (2007). Toward a Hybrid Recommender System for E-Learning Personalization Based on Web Usage Mining Techniques and Information Retrieval. E-Learn: World Conference on E-Learning in Corporate, Government, Healthcare, and Higher Education. 2007(1). 6136–6145. 16 indexed citations
16.
Zhang, Haizheng, Bamshad Mobasher, C. Lee Giles, et al.. (2007). Proceedings of the 9th WebKDD and 1st SNA-KDD 2007 workshop on Web mining and social network analysis. Knowledge Discovery and Data Mining. 82 indexed citations
17.
Mobasher, Bamshad, Olfa Nasraoui, Bing Liu, & Brij Masand. (2006). Advances in Web Mining and Web Usage Analysis: 6th International Workshop on Knowledge Discovery on the Web, WEBKDD 2004Seattle, WA, USA, August 22-25, ... Papers (Lecture Notes in Computer Science). 1 indexed citations
18.
Nasraoui, Olfa, Myra Spiliopoulou, Jaideep Srivastava, Bamshad Mobasher, & Brij Masand. (2006). Proceedings of the 8th Knowledge discovery on the web international conference on Advances in web mining and web usage analysis. 3 indexed citations
19.
Nasraoui, Olfa, Hichem Frigui, & James M. Keller. (2003). Proceedings of the 12th IEEE International Conference on Fuzzy Systems : Sunday 25 May-Wednesday 28 May, 2003, St. Louis, Missouri, USA : exploring new frontiers : FUZZ-IEEE 2003. 2 indexed citations
20.
Nasraoui, Olfa, et al.. (2003). Mining Evolving User Profiles in Noisy Web Clickstream Data with a Scalable Immune System Clustering Algorithm. 18 indexed citations

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.

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