Eduard Dragut

1.0k total citations
63 papers, 527 citations indexed

About

Eduard Dragut is a scholar working on Artificial Intelligence, Information Systems and Computer Networks and Communications. According to data from OpenAlex, Eduard Dragut has authored 63 papers receiving a total of 527 indexed citations (citations by other indexed papers that have themselves been cited), including 40 papers in Artificial Intelligence, 29 papers in Information Systems and 15 papers in Computer Networks and Communications. Recurrent topics in Eduard Dragut's work include Web Data Mining and Analysis (23 papers), Topic Modeling (19 papers) and Sentiment Analysis and Opinion Mining (15 papers). Eduard Dragut is often cited by papers focused on Web Data Mining and Analysis (23 papers), Topic Modeling (19 papers) and Sentiment Analysis and Opinion Mining (15 papers). Eduard Dragut collaborates with scholars based in United States, Qatar and Germany. Eduard Dragut's co-authors include Clement Yu, Weiyi Meng, Prasad Sistla, Ulf Leser, Arjun Mukherjee, Slobodan Vučetić, Fan Yang, Fang Fang, Mourad Ouzzani and Christiane Fellbaum and has published in prestigious journals such as IEEE Access, IEEE Transactions on Knowledge and Data Engineering and Computers & Geosciences.

In The Last Decade

Eduard Dragut

55 papers receiving 482 citations

Peers

Eduard Dragut
Rongjing Xiang United States
Jack Muramatsu United States
Grace Hui Yang United States
Eduard Dragut
Citations per year, relative to Eduard Dragut Eduard Dragut (= 1×) peers Paul‐Alexandru Chirita

Countries citing papers authored by Eduard Dragut

Since Specialization
Citations

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

Fields of papers citing papers by Eduard Dragut

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Eduard Dragut

This figure shows the co-authorship network connecting the top 25 collaborators of Eduard Dragut. A scholar is included among the top collaborators of Eduard Dragut 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 Eduard Dragut. Eduard Dragut 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
3.
Holyfield, Christine, et al.. (2024). Leveraging Communication Partner Speech to Automate Augmented Input for Children on the Autism Spectrum Who Are Minimally Verbal: Prototype Development and Preliminary Efficacy Investigation. American Journal of Speech-Language Pathology. 33(3). 1174–1192. 10 indexed citations
4.
Lorah, Elizabeth R., et al.. (2024). Spurring Innovation in AAC Technology through Collaborative Dreaming and Needs Finding with Individuals with Developmental Disabilities Who Use AAC. Seminars in Speech and Language. 45(5). 461–474. 1 indexed citations
5.
Dragut, Eduard, et al.. (2023). Learning To Rank Resources with GNN. arXiv (Cornell University). 3247–3256. 3 indexed citations
6.
Tincani, Matt, et al.. (2023). Vocational Interventions for Individuals with ASD: Umbrella Review. Review Journal of Autism and Developmental Disorders. 11(4). 806–842. 4 indexed citations
7.
Pavlovski, Martin, et al.. (2023). Aligning Comments to News Articles on a Budget. IEEE Access. 11. 18900–18909. 1 indexed citations
8.
Zhang, Qi, et al.. (2023). DMDD: A Large-Scale Dataset for Dataset Mentions Detection. Transactions of the Association for Computational Linguistics. 11. 1132–1146. 2 indexed citations
9.
Shen, Chen, Chao Han, Lihong He, et al.. (2022). Session-based News Recommendation from Temporal User Commenting Dynamics. 6. 163–170. 1 indexed citations
10.
Dragut, Eduard, et al.. (2021). On the Usefulness of Personality Traits in Opinion-oriented Tasks. 547–556. 1 indexed citations
11.
Zhang, Yifan, et al.. (2021). Opinion Prediction with User Fingerprinting. 1423–1431. 1 indexed citations
12.
Dragut, Eduard, Yunyao Li, Lucian Popa, & Slobodan Vučetić. (2021). Data Science with Human in the Loop. 4123–4124.
13.
Mukherjee, Arjun, et al.. (2019). On the dynamics of user engagement in news comment media. Wiley Interdisciplinary Reviews Data Mining and Knowledge Discovery. 10(1). 14 indexed citations
14.
Dragut, Eduard, et al.. (2019). Biased News Data Influence on Classifying Social Media Posts.. International ACM SIGIR Conference on Research and Development in Information Retrieval. 3–8. 1 indexed citations
15.
Dong, Yongquan, Eduard Dragut, & Weiyi Meng. (2018). Normalization of Duplicate Records from Multiple Sources. IEEE Transactions on Knowledge and Data Engineering. 31(4). 769–782. 11 indexed citations
16.
Mukherjee, Arjun, et al.. (2018). Leveraging Social Media Signals for Record Linkage. 1195–1204. 3 indexed citations
17.
Yang, Fan, Arjun Mukherjee, & Eduard Dragut. (2017). Satirical News Detection and Analysis using Attention Mechanism and Linguistic Features. 1979–1989. 27 indexed citations
18.
Dragut, Eduard & Christiane Fellbaum. (2014). The Role of Adverbs in Sentiment Analysis. 38–41. 16 indexed citations
19.
Dragut, Eduard, et al.. (2013). YumiInt — A deep Web integration system for local search engines for Geo-referenced objects. 1352–1355. 1 indexed citations
20.
Dragut, Eduard, Clement Yu, & Weiyi Meng. (2006). Meaningful labeling of integrated query interfaces. Very Large Data Bases. 679–690. 14 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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