Nayer Wanas

696 total citations
34 papers, 447 citations indexed

About

Nayer Wanas is a scholar working on Artificial Intelligence, Information Systems and Computer Vision and Pattern Recognition. According to data from OpenAlex, Nayer Wanas has authored 34 papers receiving a total of 447 indexed citations (citations by other indexed papers that have themselves been cited), including 27 papers in Artificial Intelligence, 13 papers in Information Systems and 7 papers in Computer Vision and Pattern Recognition. Recurrent topics in Nayer Wanas's work include Topic Modeling (8 papers), Neural Networks and Applications (8 papers) and Intelligent Tutoring Systems and Adaptive Learning (8 papers). Nayer Wanas is often cited by papers focused on Topic Modeling (8 papers), Neural Networks and Applications (8 papers) and Intelligent Tutoring Systems and Adaptive Learning (8 papers). Nayer Wanas collaborates with scholars based in Egypt, Canada and United States. Nayer Wanas's co-authors include Mohamed S. Kamel, G. Auda, Fakhri Karray, Amr Magdy, Motaz El-Saban, Waleed Ammar, Rozita Dara, Hanan Elazhary, Fakhri Karray and Samir I. Shaheen and has published in prestigious journals such as SHILAP Revista de lepidopterología, Pattern Recognition and Pattern Recognition Letters.

In The Last Decade

Nayer Wanas

33 papers receiving 426 citations

Peers

Nayer Wanas
Comparison fields: 5 of 94
  • Artificial Intelligence 228
  • Information Systems 147
  • Computer Vision and Pattern Recognition 63
  • Sociology and Political Science 56
  • Computer Networks and Communications 38
Francesco Cauteruccio Italy
Enyan Dai United States
Jie Wen China
Ainur Yessenalina United States
Marcin Korytkowski Poland
Suhrid Balakrishnan United States
Kaize Shi China
Hancheng Ge United States
Francesco Cauteruccio Italy View profile →
Citations per field, relative to Nayer Wanas
Nayer Wanas · 1×
Citations per year, relative to Nayer Wanas
Nayer Wanas · 1×

Countries citing papers authored by Nayer Wanas

Since Specialization
Citations

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

Fields of papers citing papers by Nayer Wanas

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Nayer Wanas

This figure shows the co-authorship network connecting the top 25 collaborators of Nayer Wanas. A scholar is included among the top collaborators of Nayer Wanas 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 Nayer Wanas. Nayer Wanas 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
# Title Journal Authors Indexed citations
1 Unsupervised Domain Adaptation via Weighted Sequential Discriminative Feature Learning for Sentiment Analysis Applied Sciences Nayer Wanas, Magda B. Fayek et al. 3
2 Unsupervised domain adaptation with post-adaptation labeled domain performance preservation SHILAP Revista de lepidopterología Nayer Wanas, Magda B. Fayek et al. 2
3 DETECTION AND HANDLING OF DIFFERENT TYPES OF CONCEPT DRIFT IN NEWS RECOMMENDATION SYSTEMS International Journal of Computer Science and Information Technology Nayer Wanas, Ahmed Farouk et al. 9
4 Constraint-based Student Modelling in Probability Story Problems with Scaffolding Techniques International Journal of Emerging Technologies in Learning (iJET) Nayer Wanas, Hanan Elazhary et al. 10
5 Generating story problems via controlled parameters in a web-based intelligent tutoring system International Journal of Information and Learning Technology Hanan Elazhary, Nayer Wanas et al. 14
6 Proactive scheduling for content pre-fetching in mobile networks John Tadrous, H. El Gamal et al. 11
7 PAUL Hesham El Gamal, Tamer ElBatt et al. 1
8 Clustering Posts in Online Discussion Forum Threads International Journal of Computer Science and Information Technology Nayer Wanas et al. 7
9 PUT-Tag: personalized user-centric tag recommendation for social bookmarking systems Social Network Analysis and Mining Nayer Wanas et al. 20
10 Inferring the Differential Student Model in a Probabilistic Domain Using Abduction inference in Bayesian networks Nayer Wanas et al. 4
11 A Dynamic Load Balancing Framework for Real-time Applications in Message Passing Systems International Journal of Parallel Programming Nayer Wanas, Samir I. Shaheen et al. 12
12 Web-based statistical fact checking of textual documents Amr Magdy, Nayer Wanas 37
13 A Study of Text Preprocessing Tools for Arabic Text Categorization Nayer Wanas et al. 38
14 Egypt Chapter Report [Family Corner] IEEE Computational Intelligence Magazine Hani Hagras, Rabie Α. Ramadan et al. 1
15 Using automatic keyword extraction to detect off-topic posts in online discussion boards Nayer Wanas, Amr Magdy et al. 4
16 A study of local and global thresholding techniques in text categorization Nayer Wanas et al. 9
17 Weighted combination of neural network ensembles Nayer Wanas, Mohamed S. Kamel 3
18 Feature-based architectures for decision fusion Mohamed S. Kamel, Fakhri Karray et al. 13
19 On the optimal number of hidden nodes in a neural network Nayer Wanas, G. Auda et al. 107
20 Decision fusion in neural network ensembles Nayer Wanas, Mohamed S. Kamel 18

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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