Anna Tordai

475 total citations
17 papers, 267 citations indexed

About

Anna Tordai is a scholar working on Artificial Intelligence, Molecular Biology and Information Systems. According to data from OpenAlex, Anna Tordai has authored 17 papers receiving a total of 267 indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Artificial Intelligence, 3 papers in Molecular Biology and 3 papers in Information Systems. Recurrent topics in Anna Tordai's work include Semantic Web and Ontologies (13 papers), Natural Language Processing Techniques (4 papers) and Digital Humanities and Scholarship (3 papers). Anna Tordai is often cited by papers focused on Semantic Web and Ontologies (13 papers), Natural Language Processing Techniques (4 papers) and Digital Humanities and Scholarship (3 papers). Anna Tordai collaborates with scholars based in Netherlands, Italy and United Kingdom. Anna Tordai's co-authors include Jacco van Ossenbruggen, Guus Schreiber, Borys Omelayenko, Valentina Presutti, Bob Wielinga, Victor de Boer, Alia Amin, Jan Wielemaker, Michiel Hildebrand and Lora Aroyo and has published in prestigious journals such as Lecture notes in computer science, Journal of Web Semantics and Communications in computer and information science.

In The Last Decade

Anna Tordai

17 papers receiving 237 citations

Peers

Anna Tordai
Comparison fields: 5 of 48
  • Artificial Intelligence 206
  • Information Systems 110
  • Computer Vision and Pattern Recognition 44
  • Molecular Biology 39
  • Management Science and Operations Research 31
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Citations per field, relative to Anna Tordai
Anna Tordai · 1×
Citations per year, relative to Anna Tordai
Anna Tordai · 1×

Countries citing papers authored by Anna Tordai

Since Specialization
Citations

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

Fields of papers citing papers by Anna Tordai

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Anna Tordai

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

All Works

17 of 17 papers shown
# Work Indexed citations
1
Elsevier's healthcare knowledge graph and the case for enterprise level linked data standards
2
2
Semantic Web Challenges: Third SemWebEval Challenge at ESWC 2016, Heraklion, Crete, Greece, May 29 - June 2, 2016, Revised Selected Papers
4
3 7
4 6
5 35
6 41
7 31
8 9
9
Aligning large SKOS-like vocabularies
1
10
Lost in translation? empirical analysis of mapping compositions for large ontologies
7
11 7
12 1
13 81
14
Searching and Annotating Virtual Heritage Collections with Semantic-Web Techniques
17
15 5
16
Semantic Excavation of the City of Books
9
17
Hungarian Monolingual Retrieval at CLEF 2005
4

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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