Georgeta Bordea

1.3k citations
22 papers · 251 · h-index 7

Impact in

Papers in

    • Topic Modeling 9
    • Semantic Web and Ontologies 5
    • Natural Language Processing Techniques 4
    • Advanced Text Analysis Techniques 3
    • Biomedical Text Mining and Ontologies 6

Georgeta Bordea

21 papers receiving 232 citations

Peers

Georgeta Bordea
Comparison fields: 5 of 47
  • Artificial Intelligence 208
  • Computer Science Applications 13
  • Information Systems 49
  • Management Science and Operations Research 19
  • Information Systems and Management 10
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Citations per year

Countries citing papers authored by Georgeta Bordea

Since Specialization
Citations

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

Fields of papers citing papers by Georgeta Bordea

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 22 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201557
2 201656
3 201638
4
Forecasting emerging trends from scientific literature
201619
5 201613
6
DERIUNLP: A Context Based Approach to Automatic Keyphrase Extraction
201010
7 20218
8 20136
9 20156
10 20146
11 20136
12
Expertise Mining for Enterprise Content Management
20125
13 20125
14 20224
15 20103
16 20193
17 20192
18
The Categories of Philosophy in the Digital Era.
20161
19
Semi-Supervised Technical Term Tagging With Minimal User Feedback
20121
20 20241

About Georgeta Bordea

Georgeta Bordea is a scholar working on Artificial Intelligence, Molecular Biology, Information Systems, Computational Theory and Mathematics and Computer Science Applications, having authored 22 papers that have together received 251 indexed citations. Recurring topics across this work include Topic Modeling (9 papers), Biomedical Text Mining and Ontologies (6 papers), Semantic Web and Ontologies (5 papers), Expert finding and Q&A systems (5 papers), Natural Language Processing Techniques (4 papers), Advanced Text Analysis Techniques (3 papers), Computational Drug Discovery Methods (2 papers) and Mobile Crowdsensing and Crowdsourcing (2 papers). The work is most often cited by research in Artificial Intelligence (208 citations), Computer Science Applications (13 citations), Information Systems (49 citations), Management Science and Operations Research (19 citations) and Information Systems and Management (10 citations). Georgeta Bordea has collaborated with scholars based in Ireland, France and Italy. Frequent co-authors include Paul Buitelaar, Els Lefever, Roberto Navigli, Stefano Faralli, Gayo Diallo, Toine Bogers, Gianmaria Silvello, Nicola Ferro, Tudor Groza and Barry Coughlan. Their work appears in journals such as Language Resources and Evaluation, Yearbook of Medical Informatics, Semantic Web, Journal of Biomedical Semantics and International Journal on Digital Libraries.

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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