Mariam Daoud

571 citations
18 papers · 275 · h-index 9

Impact in

Papers in

Mariam Daoud

18 papers receiving 254 citations

Peers

Mariam Daoud
Comparison fields: 5 of 42
  • Information Systems 175
  • Artificial Intelligence 143
  • Signal Processing 47
  • Computer Vision and Pattern Recognition 78
  • Computer Science Applications 16
Replace Roberto Mirizzi with:
Roberto Mirizzi Italy
Mouna Kacimi Italy
Pu‐Jen Cheng Taiwan
Ahu Sieg United States
Van Dang United States
Cheng Xiang Zhai United States
Cosimo Palmisano Italy
Hajer Baazaoui Zghal Tunisia
Jonathan L. Elsas United States
Mariam Daoud relative to Roberto Mirizzi Italy Roberto Mirizzi's profile →
Citations per field
00.5×1.5×1.9×
Roberto Mirizzi · 1×
Citations per year

Countries citing papers authored by Mariam Daoud

Since Specialization
Citations

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

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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.

Border = papers with Mariam Daoud Line = papers co-authored together Mariam Daoud links everyone, so they are left out of the graph.

All Works

18 of 18 papers shown
#Work
1 200980
2 200942
3 200926
4 200824
5 201316
6 201216
7 201811
8 201110
9
Using A Concept-based User Context For Search Personalization
20089
10
York University at TREC 2011: Medical Records Track
20118
11 20188
12
Contextual query classification in web search.
20086
13 20135
14 20175
15 20134
16 20082
17 20102
18
Contextual evaluation of mobile search
20101

About Mariam Daoud

Mariam Daoud is a scholar working on Information Systems, Artificial Intelligence, Computer Vision and Pattern Recognition, Molecular Biology and Signal Processing, having authored 18 papers that have together received 275 indexed citations. Recurring topics across this work include Information Retrieval and Search Behavior (9 papers), Web Data Mining and Analysis (6 papers), Semantic Web and Ontologies (4 papers), Biomedical Text Mining and Ontologies (4 papers), Image Retrieval and Classification Techniques (4 papers), Advanced Image and Video Retrieval Techniques (4 papers), Recommender Systems and Techniques (4 papers) and Data Management and Algorithms (3 papers). The work is most often cited by research in Information Systems (175 citations), Artificial Intelligence (143 citations), Signal Processing (47 citations), Computer Vision and Pattern Recognition (78 citations) and Computer Science Applications (16 citations). Mariam Daoud has collaborated with scholars based in France, Canada and Tunisia. Frequent co-authors include Mohand Boughanem, Jimmy Xiangji Huang, Lynda Tamine, 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, ACM Computing Surveys, Journal of Information Science and Text REtrieval Conference.

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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