Riyad Al–Shalabi
- Artificial Intelligence top 2%
- Advanced Text Analysis Techniques 9
- Text and Document Classification Technologies 9
- Natural Language Processing Techniques 8
- Topic Modeling 7
- Sentiment Analysis and Opinion Mining 6
- Algorithms and Data Compression 6
- Information Systems top 5%
- Spam and Phishing Detection 6
- Information Retrieval and Search Behavior 5
- Co-authors
- Ghassan KanaanMahmoud Al‐AyyoubMartha EvensSameh GhwanmehMohammed A. ShehabMohammed ElbesTarek KananAla Mughaid
In The Last Decade
Riyad Al–Shalabi
36 papers receiving 542 citations
Peers
Comparison fields: 5 of 68
- Artificial Intelligence 507
- Information Systems 208
- Computer Vision and Pattern Recognition 44
- Health Information Management 8
- Computer Networks and Communications 29
Countries citing papers authored by Riyad Al–Shalabi
This map shows the geographic impact of Riyad Al–Shalabi'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 Riyad Al–Shalabi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Riyad Al–Shalabi more than expected).
Fields of papers citing papers by Riyad Al–Shalabi
This network shows the impact of papers produced by Riyad Al–Shalabi. 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 Riyad Al–Shalabi. The network helps show where Riyad Al–Shalabi may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Riyad Al–Shalabi, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2022 | 30 | |
| 2 | 2022 | 27 | |
| 3 | 2022 | 0 | |
| 4 | 2022 | 1 | |
| 5 | 2022 | 2 | |
| 6 | 2022 | 1 | |
| 7 | 2021 | 6 | |
| 8 | Improved hierarchical classifiers for multi-way sentiment analysis. | 2017 | 8 |
| 9 | 2017 | 3 | |
| 10 | Building an effective rule-based light stemmer for arabic language to improve search effectiveness. | 2012 | 39 |
| 11 | 2009 | 7 | |
| 12 | 2009 | 13 | |
| 13 | 2007 | 3 | |
| 14 | 2006 | 6 | |
| 15 | 2006 | 10 | |
| 16 | 2004 | 1 | |
| 17 | 2004 | 7 | |
| 18 | 2004 | 30 | |
| 19 | 2004 | 3 | |
| 20 | 1998 | 63 |
About Riyad Al–Shalabi
Riyad Al–Shalabi is a scholar working on Artificial Intelligence, Information Systems, Computer Networks and Communications, Health Information Management and Computer Vision and Pattern Recognition, having authored 37 papers that have together received 595 indexed citations. Recurring topics across this work include Advanced Text Analysis Techniques (9 papers), Text and Document Classification Technologies (9 papers), Natural Language Processing Techniques (8 papers), Topic Modeling (7 papers), Spam and Phishing Detection (6 papers), Sentiment Analysis and Opinion Mining (6 papers), Algorithms and Data Compression (6 papers) and Information Retrieval and Search Behavior (5 papers). The work is most often cited by research in Artificial Intelligence (507 citations), Information Systems (208 citations), Computer Vision and Pattern Recognition (44 citations), Health Information Management (8 citations) and Computer Networks and Communications (29 citations). Riyad Al–Shalabi has collaborated with scholars based in Jordan, Bahrain and China. Frequent co-authors include Ghassan Kanaan, Mahmoud Al‐Ayyoub, Martha Evens, Sameh Ghwanmeh, Mohammed A. Shehab, Mohammed Elbes, Tarek Kanan, Ala Mughaid, Rasha M. Abd El-Aziz and Amr Abozeid. Their work appears in journals such as Applied Mathematics and Nonlinear Sciences, American Journal of Applied Sciences, Journal of Information Security and Applications, Computational Intelligence and Neuroscience and Information Technology Journal.
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.