Rada Chirkova

1.5k total citations
76 papers, 674 citations indexed

About

Rada Chirkova is a scholar working on Computer Networks and Communications, Artificial Intelligence and Signal Processing. According to data from OpenAlex, Rada Chirkova has authored 76 papers receiving a total of 674 indexed citations (citations by other indexed papers that have themselves been cited), including 51 papers in Computer Networks and Communications, 41 papers in Artificial Intelligence and 38 papers in Signal Processing. Recurrent topics in Rada Chirkova's work include Advanced Database Systems and Queries (45 papers), Data Management and Algorithms (38 papers) and Semantic Web and Ontologies (28 papers). Rada Chirkova is often cited by papers focused on Advanced Database Systems and Queries (45 papers), Data Management and Algorithms (38 papers) and Semantic Web and Ontologies (28 papers). Rada Chirkova collaborates with scholars based in United States, Greece and Chile. Rada Chirkova's co-authors include Gang Gou, Jun Yang, Dan Suciu, Alon Halevy, Yahya Fathi, Yannis Viniotis, Chen Li, Alexander Tropsha, Foto Afrati and Timothy G. Mattson and has published in prestigious journals such as Bioinformatics, Drug Discovery Today and IEEE Transactions on Knowledge and Data Engineering.

In The Last Decade

Rada Chirkova

65 papers receiving 621 citations

Peers

Rada Chirkova
Sven Groppe Germany
Gaurav Bhalotia United States
Rada Chirkova
Citations per year, relative to Rada Chirkova Rada Chirkova (= 1×) peers David Toman

Countries citing papers authored by Rada Chirkova

Since Specialization
Citations

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

Fields of papers citing papers by Rada Chirkova

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Rada Chirkova

This figure shows the co-authorship network connecting the top 25 collaborators of Rada Chirkova. A scholar is included among the top collaborators of Rada Chirkova 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 Rada Chirkova. Rada Chirkova 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
4.
Korn, Daniel, Vinícius M. Alves, Joyce Villa Verde Bastos Borba, et al.. (2022). Defining clinical outcome pathways. Drug Discovery Today. 27(6). 1671–1678. 9 indexed citations
5.
Zheng, Weifan, et al.. (2021). Learning Drug-Disease-Target Embedding (DDTE) from knowledge graphs to inform drug repurposing hypotheses. Journal of Biomedical Informatics. 119. 103838–103838. 24 indexed citations
6.
Chirkova, Rada, Jon Doyle, & Juan L. Reutter. (2021). Ensuring Data Readiness for Quality Requirements with Help from Procedure Reuse. Journal of Data and Information Quality. 13(3). 1–15. 3 indexed citations
7.
Melo‐Filho, Cleber C., et al.. (2021). Explaining Drug-Discovery Hypotheses Using Knowledge-Graph Patterns. 2021 IEEE International Conference on Big Data (Big Data). 3709–3716. 3 indexed citations
8.
Alves, Vinícius M., Daniel Korn, Stephen J. Capuzzi, et al.. (2021). Knowledge-based approaches to drug discovery for rare diseases. Drug Discovery Today. 27(2). 490–502. 26 indexed citations
9.
Korn, Daniel, Tesia Bobrowski, Patrick Wang, et al.. (2020). COVID-KOP: integrating emerging COVID-19 data with the ROBOKOP database. Bioinformatics. 37(4). 586–587. 15 indexed citations
10.
Chirkova, Rada, et al.. (2017). Enabling query processing across heterogeneous data models: A survey. 3211–3220. 26 indexed citations
11.
Ajmeri, Nirav, et al.. (2016). Coco: runtime reasoning about conflicting commitments. Explore Bristol Research. 17–23. 9 indexed citations
12.
Chen, Ling, Ting Yu, & Rada Chirkova. (2015). WaveCluster with Differential Privacy. 1011–1020. 4 indexed citations
13.
Chirkova, Rada. (2015). Combined-semantics equivalence of conjunctive queries: Decidability and tractability results. Journal of Computer and System Sciences. 82(3). 395–465. 2 indexed citations
14.
Afrati, Foto & Rada Chirkova. (2010). Selecting and using views to compute aggregate queries. Journal of Computer and System Sciences. 77(6). 1079–1107. 3 indexed citations
15.
Fathi, Yahya, et al.. (2010). Exact and inexact methods for solving the view and index selection problem for olap performance improvement. 1 indexed citations
16.
Chirkova, Rada & George Fletcher. (2009). Towards Well-Behaved Schema Evolution. NCSU Libraries Repository (North Carolina State University Libraries). 4 indexed citations
18.
Chirkova, Rada, et al.. (2008). Exact and inexact methods for selecting views and indexes for OLAP performance improvement. NCSU Libraries Repository (North Carolina State University Libraries). 311–322. 12 indexed citations
19.
Afrati, Foto & Rada Chirkova. (2005). Selecting and Using Views to Compute Aggregate Queries (Extended Abstract). DSpace - NTUA (National Technical University of Athens). 383–397. 8 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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