Fatiha Sadat
About
In The Last Decade
Fatiha Sadat
60 papers receiving 581 citations
Peers
Comparison fields: 5 of 48
- Artificial Intelligence 634
- Information Systems 88
- Computer Vision and Pattern Recognition 65
- Language and Linguistics 57
- Molecular Biology 33
Countries citing papers authored by Fatiha Sadat
This map shows the geographic impact of Fatiha Sadat'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 Fatiha Sadat with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Fatiha Sadat more than expected).
Fields of papers citing papers by Fatiha Sadat
This network shows the impact of papers produced by Fatiha Sadat. 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 Fatiha Sadat. The network helps show where Fatiha Sadat may publish in the future.
Co-authorship network of co-authors of Fatiha Sadat
This figure shows the co-authorship network connecting the top 25 collaborators of Fatiha Sadat. A scholar is included among the top collaborators of Fatiha Sadat 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 Fatiha Sadat. Fatiha Sadat is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 0 | |
| 3 | 1 | |
| 4 | 2 | |
| 5 | Low-Resource NMT: an Empirical Study on the Effect of Rich Morphological Word Segmentation on Inuktitut | 4 |
| 6 | Hybrid Statistical and Attentive Deep Neural Approach for Named Entity Recognition in Historical Newspapers. | 1 |
| 7 | Augmenting Named Entity Recognition with Commonsense Knowledge | 2 |
| 8 | 4 | |
| 9 | Using Neural Transfer Learning for Morpho-syntactic Tagging of South-Slavic Languages Tweets | 4 |
| 10 | 8 | |
| 11 | UQAM-NTL: Named entity recognition in Twitter messages. | 3 |
| 12 | Named Entity Recognition and Hashtag Decomposition to Improve the Classification of Tweets | 14 |
| 13 | Lexfom: a lexical functions ontology model | 3 |
| 14 | 7 | |
| 15 | 55 | |
| 16 | 39 | |
| 17 | Towards a Hybrid Rule-based and Statistical Arabic-French Machine Translation System | 2 |
| 18 | Exploiting a Multilingual Web-based Encyclopedia for Bilingual Terminology Extraction | 1 |
| 19 | 18 | |
| 20 | Exploiting and Combining Multiple Resources for Query Expansion in Cross - Language Information Retrieval | 1 |
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.