Mariam Daoud
Impact in
- Information Systems top 5%
- Recommender Systems and Techniques
- Information Retrieval and Search Behavior
- Web Data Mining and Analysis
- Artificial Intelligence top 10%
- Semantic Web and Ontologies
- Topic Modeling
Papers in
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- Information Retrieval and Search Behavior 10
- Web Data Mining and Analysis 8
- Recommender Systems and Techniques 4
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- Semantic Web and Ontologies 7
- Co-authors
- Mohand Boughanem (11 shared papers)Lynda Tamine (7 shared papers)Jimmy Xiangji Huang (9 shared papers)Maher Ben Jemaa (4 shared papers)Jun Miao (1 shared paper)
In The Last Decade
Mariam Daoud
23 papers receiving 388 citations
Peers
Comparison fields: 5 of 47
- Information Systems 278
- Artificial Intelligence 211
- Signal Processing 68
- Computer Vision and Pattern Recognition 120
- Computer Science Applications 21
Countries citing papers authored by Mariam Daoud
This map shows the geographic impact of Mariam Daoud'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 Mariam Daoud with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mariam Daoud more than expected).
Fields of papers citing papers by Mariam Daoud
This network shows the impact of papers produced by Mariam Daoud. 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 Mariam Daoud. The network helps show where Mariam Daoud may publish in the future.
Co-authors
The 5 scholars most cited alongside Mariam Daoud, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 23 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2009 | 115 | |
| 2 | 2009 | 56 | |
| 3 | 2009 | 37 | |
| 4 | 2010 | 28 | |
| 5 | 2008 | 26 | |
| 6 | 2018 | 18 | |
| 7 | 2013 | 17 | |
| 8 | 2012 | 16 | |
| 9 | 2013 | 16 | |
| 10 | 2007 | 13 | |
| 11 | 2011 | 12 | |
| 12 | 2018 | 11 | |
| 13 | Using A Concept-based User Context For Search Personalization | 2008 | 11 |
| 14 | York University at TREC 2011: Medical Records Track | 2011 | 9 |
| 15 | Contextual query classification in web search. | 2008 | 8 |
| 16 | 2017 | 6 | |
| 17 | 2013 | 6 | |
| 18 | 2013 | 5 | |
| 19 | 2008 | 4 | |
| 20 | 2009 | 4 |
About Mariam Daoud
Mariam Daoud is a scholar working on Information Systems, Artificial Intelligence, Computer Vision and Pattern Recognition, Signal Processing and Molecular Biology, having authored 23 papers that have together received 425 indexed citations. Recurring topics across this work include Information Retrieval and Search Behavior (10 papers), Web Data Mining and Analysis (8 papers), Semantic Web and Ontologies (7 papers), Image Retrieval and Classification Techniques (6 papers), Advanced Image and Video Retrieval Techniques (5 papers), Data Management and Algorithms (5 papers), Recommender Systems and Techniques (4 papers) and Biomedical Text Mining and Ontologies (4 papers). The work is most often cited by research in Information Systems (278 citations), Artificial Intelligence (211 citations), Signal Processing (68 citations), Computer Vision and Pattern Recognition (120 citations) and Computer Science Applications (21 citations). Mariam Daoud has collaborated with scholars based in France, Canada and Tunisia. Frequent co-authors include Mohand Boughanem, Lynda Tamine, Jimmy Xiangji Huang, Maher Ben Jemaa and Jun Miao. Their work appears in journals such as Journal of the Association for Information Science and Technology, Knowledge and Information Systems, Journal of Information Science, ACM Computing Surveys and Lecture notes in computer science.
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.