Nabil Alami

510 total citations
22 papers, 275 citations indexed

About

Nabil Alami is a scholar working on Artificial Intelligence, Information Systems and Sociology and Political Science. According to data from OpenAlex, Nabil Alami has authored 22 papers receiving a total of 275 indexed citations (citations by other indexed papers that have themselves been cited), including 20 papers in Artificial Intelligence, 11 papers in Information Systems and 4 papers in Sociology and Political Science. Recurrent topics in Nabil Alami's work include Sentiment Analysis and Opinion Mining (11 papers), Topic Modeling (11 papers) and Recommender Systems and Techniques (11 papers). Nabil Alami is often cited by papers focused on Sentiment Analysis and Opinion Mining (11 papers), Topic Modeling (11 papers) and Recommender Systems and Techniques (11 papers). Nabil Alami collaborates with scholars based in Morocco, Bangladesh and Spain. Nabil Alami's co-authors include Mohammed Meknassi, Noureddine En-Nahnahi, Mostafa El Mallahi, Saïd Ouatik El Alaoui, Hassan Qjidaa, Mohamed Lazaar and Horacio Rodríguez and has published in prestigious journals such as SHILAP Revista de lepidopterología, Expert Systems with Applications and Neurocomputing.

In The Last Decade

Nabil Alami

17 papers receiving 257 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Nabil Alami Morocco 9 222 71 20 16 13 22 275
Prafulla Bafna India 8 182 0.8× 83 1.2× 12 0.6× 20 1.3× 8 0.6× 27 252
Deqing Yang China 9 177 0.8× 120 1.7× 35 1.8× 13 0.8× 28 2.2× 34 232
Md Mehrab Tanjim United States 5 135 0.6× 79 1.1× 22 1.1× 20 1.3× 26 2.0× 8 232
Viet-Man Le Austria 8 79 0.4× 86 1.2× 15 0.8× 13 0.8× 15 1.2× 27 164
Rianne Kaptein Netherlands 10 170 0.8× 116 1.6× 18 0.9× 15 0.9× 13 1.0× 29 219
Wenxiong Liao China 8 197 0.9× 28 0.4× 27 1.4× 12 0.8× 14 1.1× 16 271
Kaisong Song China 11 282 1.3× 71 1.0× 33 1.6× 20 1.3× 14 1.1× 28 315
Anh-Cuong Le Vietnam 8 254 1.1× 61 0.9× 23 1.1× 35 2.2× 19 1.5× 32 303
Siyu Wang China 6 163 0.7× 57 0.8× 25 1.3× 22 1.4× 24 1.8× 23 249
Zhendong Dong China 4 291 1.3× 53 0.7× 22 1.1× 8 0.5× 18 1.4× 4 325

Countries citing papers authored by Nabil Alami

Since Specialization
Citations

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

Fields of papers citing papers by Nabil Alami

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Nabil Alami

This figure shows the co-authorship network connecting the top 25 collaborators of Nabil Alami. A scholar is included among the top collaborators of Nabil Alami 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 Nabil Alami. Nabil Alami 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
1.
Alami, Nabil, et al.. (2025). A hybrid approach combining sentiment analysis and deep learning to mitigate data sparsity in recommender systems. Neurocomputing. 636. 129886–129886. 1 indexed citations
2.
Alami, Nabil, et al.. (2025). Advancing recommendation systems with DeepMF and hybrid sentiment analysis: Deep learning and Lexicon-based integration. Expert Systems with Applications. 279. 127432–127432. 1 indexed citations
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Alami, Nabil, et al.. (2024). Integrated sentiment analysis with BERT for enhanced hybrid recommendation systems. Expert Systems with Applications. 261. 125533–125533. 12 indexed citations
5.
Alami, Nabil, et al.. (2024). Optimizing Hybrid Recommendations: VADER-Enhanced Sentiment Analysis. 1–7. 2 indexed citations
6.
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8.
Alami, Nabil, et al.. (2024). Addressing data sparsity and cold-start challenges in recommender systems using advanced deep learning and self-supervised learning techniques. Journal of Experimental & Theoretical Artificial Intelligence. 37(8). 1421–1451.
9.
Alami, Nabil, et al.. (2024). Detecting trending products through moving average and sentiment analysis. Multimedia Tools and Applications. 84(13). 12141–12162. 3 indexed citations
10.
Alami, Nabil, et al.. (2023). Enhancing Collaborative Filtering-Based Recommender System Using Sentiment Analysis. Future Internet. 15(7). 235–235. 25 indexed citations
11.
Alami, Nabil, et al.. (2023). Recommendation system using Deep Learning-based sentiment analysis. 41–47. 6 indexed citations
12.
Alami, Nabil, et al.. (2023). BERT-enhanced sentiment analysis for personalized e-commerce recommendations. Multimedia Tools and Applications. 83(19). 56463–56488. 18 indexed citations
13.
En-Nahnahi, Noureddine, et al.. (2021). Arabic Biomedical Community Question Answering Based on Contextualized Embeddings. International Journal of Intelligent Information Technologies. 17(3). 1–17.
14.
Alami, Nabil, et al.. (2021). Hybrid method for text summarization based on statistical and semantic treatment. Multimedia Tools and Applications. 80(13). 19567–19600. 18 indexed citations
15.
Alami, Nabil, et al.. (2021). Unsupervised neural networks for automatic Arabic text summarization using document clustering and topic modeling. Expert Systems with Applications. 172. 114652–114652. 44 indexed citations
16.
Alami, Nabil, Mohammed Meknassi, & Noureddine En-Nahnahi. (2019). Enhancing unsupervised neural networks based text summarization with word embedding and ensemble learning. Expert Systems with Applications. 123. 195–211. 77 indexed citations
17.
Alami, Nabil, Noureddine En-Nahnahi, Saïd Ouatik El Alaoui, & Mohammed Meknassi. (2018). Using Unsupervised Deep Learning for Automatic Summarization of Arabic Documents. Arabian Journal for Science and Engineering. 43(12). 7803–7815. 25 indexed citations
18.
Alami, Nabil, Mohammed Meknassi, Saïd Ouatik El Alaoui, & Noureddine En-Nahnahi. (2016). Impact of stemming on Arabic text summarization. 338–343. 11 indexed citations
19.
Alami, Nabil, et al.. (2015). Automatic Texts Summarization: Current State of the Art. Journal of Asian Scientific Research. 5(1). 1–15. 8 indexed citations
20.
Alami, Nabil, Mohammed Meknassi, Saïd Ouatik El Alaoui, & Noureddine En-Nahnahi. (2015). Arabic text summarization based on graph theory. 15 indexed citations

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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