Aghiles Salah

547 total citations
14 papers, 305 citations indexed

About

Aghiles Salah is a scholar working on Artificial Intelligence, Information Systems and Computer Vision and Pattern Recognition. According to data from OpenAlex, Aghiles Salah has authored 14 papers receiving a total of 305 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Artificial Intelligence, 9 papers in Information Systems and 7 papers in Computer Vision and Pattern Recognition. Recurrent topics in Aghiles Salah's work include Recommender Systems and Techniques (9 papers), Topic Modeling (5 papers) and Image Retrieval and Classification Techniques (4 papers). Aghiles Salah is often cited by papers focused on Recommender Systems and Techniques (9 papers), Topic Modeling (5 papers) and Image Retrieval and Classification Techniques (4 papers). Aghiles Salah collaborates with scholars based in Singapore, France and United States. Aghiles Salah's co-authors include Mohamed Nadif, Hady W. Lauw and Quoc-Tuan Truong and has published in prestigious journals such as Neurocomputing, Journal of Machine Learning Research and Data Mining and Knowledge Discovery.

In The Last Decade

Aghiles Salah

14 papers receiving 303 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Aghiles Salah Singapore	10	210	181	107	42	30	14	305
Xuezhi Cao China	10	241 1.1×	300 1.7×	84 0.8×	71 1.7×	58 1.9×	21	408
Miguel A. Rueda-Morales Spain	6	244 1.2×	89 0.5×	97 0.9×	36 0.9×	18 0.6×	7	280
Yukihiro Tagami Japan	5	308 1.5×	309 1.7×	110 1.0×	38 0.9×	9 0.3×	15	418
Jorge Castro Spain	7	211 1.0×	105 0.6×	55 0.5×	66 1.6×	46 1.5×	11	276
Roberto Mirizzi Italy	7	268 1.3×	240 1.3×	66 0.6×	38 0.9×	15 0.5×	16	353
Zhiping Gu China	7	379 1.8×	269 1.5×	81 0.8×	86 2.0×	22 0.7×	9	413
P. Dolan United States	3	350 1.7×	214 1.2×	118 1.1×	70 1.7×	31 1.0×	3	446
Diane Hu United States	8	182 0.9×	164 0.9×	63 0.6×	57 1.4×	7 0.2×	16	286
Flavian Vasile United States	8	198 0.9×	192 1.1×	57 0.5×	83 2.0×	8 0.3×	20	290
Benjamin Kille Germany	8	209 1.0×	123 0.7×	89 0.8×	63 1.5×	14 0.5×	32	255

Countries citing papers authored by Aghiles Salah

Since Specialization

Citations

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

Fields of papers citing papers by Aghiles Salah

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Aghiles Salah

This figure shows the co-authorship network connecting the top 25 collaborators of Aghiles Salah. A scholar is included among the top collaborators of Aghiles Salah 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 Aghiles Salah. Aghiles Salah is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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14 of 14 papers shown

1.

Salah, Aghiles, et al.. (2022). Improving NMF clustering by leveraging contextual relationships among words. Neurocomputing. 495. 105–117. 7 indexed citations

2.

Truong, Quoc-Tuan, Aghiles Salah, & Hady W. Lauw. (2021). Bilateral Variational Autoencoder for Collaborative Filtering. 292–300. 45 indexed citations

3.

Salah, Aghiles, et al.. (2021). Towards Source-Aligned Variational Models for Cross-Domain Recommendation. 176–186. 16 indexed citations

4.

Truong, Quoc-Tuan, Aghiles Salah, & Hady W. Lauw. (2021). Multi-Modal Recommender Systems: Hands-On Exploration. 834–837. 15 indexed citations

5.

Truong, Quoc-Tuan, et al.. (2021). Exploring Cross-Modality Utilization in Recommender Systems. IEEE Internet Computing. 25(4). 50–57. 9 indexed citations

6.

Salah, Aghiles, et al.. (2020). Cornac: A Comparative Framework for Multimodal Recommender Systems. Journal of Machine Learning Research. 21(95). 1–5. 53 indexed citations

7.

Salah, Aghiles & Hady W. Lauw. (2018). Probabilistic Collaborative Representation Learning for Personalized Item Recommendation. Institutional Knowledge (InK) - Institutional Knowledge at Singapore Management University (Singapore Management University). 998–1008. 4 indexed citations

8.

Salah, Aghiles & Hady W. Lauw. (2018). A Bayesian Latent Variable Model of User Preferences with Item Context. 2667–2674. 5 indexed citations

9.

Salah, Aghiles, et al.. (2018). Word Co-Occurrence Regularized Non-Negative Matrix Tri-Factorization for Text Data Co-Clustering. Proceedings of the AAAI Conference on Artificial Intelligence. 32(1). 28 indexed citations

10.

Salah, Aghiles & Mohamed Nadif. (2018). Directional co-clustering. Advances in Data Analysis and Classification. 13(3). 591–620. 15 indexed citations

11.

Salah, Aghiles & Mohamed Nadif. (2017). Social regularized von Mises–Fisher mixture model for item recommendation. Data Mining and Knowledge Discovery. 31(5). 1218–1241. 15 indexed citations

12.

Salah, Aghiles, et al.. (2017). A Way to Boost Semi-NMF for Document Clustering. 2275–2278. 7 indexed citations

13.

Salah, Aghiles, et al.. (2017). Non-negative Matrix Factorization Meets Word Embedding. 1081–1084. 16 indexed citations

14.

Salah, Aghiles, et al.. (2015). A dynamic collaborative filtering system via a weighted clustering approach. Neurocomputing. 175. 206–215. 70 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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