Dan Ştefănescu

1.4k citations
53 papers · 737 · h-index 14

Impact in

    • Parallel Computing and Optimization Techniques
    • Natural Language Processing Techniques
    • Topic Modeling
    • Fuzzy Logic and Control Systems
    • Semantic Web and Ontologies
    • Advanced Text Analysis Techniques

Papers in

Dan Ştefănescu

50 papers receiving 644 citations

Peers

Dan Ştefănescu
Comparison fields: 5 of 81
  • Hardware and Architecture 158
  • Artificial Intelligence 451
  • Computer Networks and Communications 215
  • Information Systems 110
  • Software 12
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Citations per field
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Citations per year

Countries citing papers authored by Dan Ştefănescu

Since Specialization
Citations

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

Fields of papers citing papers by Dan Ştefănescu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Dan Ştefănescu, 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 Dan Ştefănescu Line = papers co-authored together Dan Ştefănescu links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 53 papers — load more, or switch the sort, to bring in the rest.

#Work
1 1998169
2 200880
3
SEMILAR: The Semantic Similarity Toolkit
201371
4 201244
5
Term Extraction, Tagging, and Mapping Tools for Under-Resourced Languages
201233
6
Hybrid Parallel Sentence Mining from Comparable Corpora
201231
7 200231
8 200827
9 199419
10 201418
11 201516
12 200915
13 201314
14
Improved Lexical Alignment by Combining Multiple Reified Alignments.
200613
15 199610
16 201410
17 19749
18 20139
19 20059
20 20068

About Dan Ştefănescu

Dan Ştefănescu is a scholar working on Artificial Intelligence, Computer Networks and Communications, Hardware and Architecture, Signal Processing and Computational Theory and Mathematics, having authored 53 papers that have together received 737 indexed citations. Recurring topics across this work include Natural Language Processing Techniques (23 papers), Topic Modeling (21 papers), Semantic Web and Ontologies (11 papers), Parallel Computing and Optimization Techniques (7 papers), Text Readability and Simplification (5 papers), Intelligent Tutoring Systems and Adaptive Learning (5 papers), Data Management and Algorithms (4 papers) and Advanced Database Systems and Queries (4 papers). The work is most often cited by research in Hardware and Architecture (158 citations), Artificial Intelligence (451 citations), Computer Networks and Communications (215 citations), Information Systems (110 citations) and Software (12 citations). Dan Ştefănescu has collaborated with scholars based in United States, Romania and Italy. Frequent co-authors include Radu Ion, Vasile Rus, Rajendra Banjade, Beatrice Lazzerini, Dan Tufiş, Nobal B. Niraula, Alessio Botta, Francesco Marcelloni, Rob H. Bisseling and Thanasis Tsantilas. Their work appears in journals such as Language Resources and Evaluation, Parallel Computing, Telecommunications Policy, Smart Learning Environments and Information Systems.

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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