Krys J. Kochut

3.5k total citations · 1 hit paper
51 papers, 1.5k citations indexed

About

Krys J. Kochut is a scholar working on Artificial Intelligence, Information Systems and Molecular Biology. According to data from OpenAlex, Krys J. Kochut has authored 51 papers receiving a total of 1.5k indexed citations (citations by other indexed papers that have themselves been cited), including 30 papers in Artificial Intelligence, 17 papers in Information Systems and 15 papers in Molecular Biology. Recurrent topics in Krys J. Kochut's work include Semantic Web and Ontologies (17 papers), Business Process Modeling and Analysis (14 papers) and Service-Oriented Architecture and Web Services (11 papers). Krys J. Kochut is often cited by papers focused on Semantic Web and Ontologies (17 papers), Business Process Modeling and Analysis (14 papers) and Service-Oriented Architecture and Web Services (11 papers). Krys J. Kochut collaborates with scholars based in United States, China and Italy. Krys J. Kochut's co-authors include Amit Sheth, John A. Miller, Jorge Cardoso, Jonathan Arnold, Mehdi Allahyari, Natarajan Kannan, Zongwei Luo, Maciej Janik, Kemafor Anyanwu and Walter D. Potter and has published in prestigious journals such as Proceedings of the National Academy of Sciences, PLoS ONE and Genetics.

In The Last Decade

Krys J. Kochut

49 papers receiving 1.3k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Quality of service for workflows and web service processes

2004 568 citations Amit Sheth, John A. Miller et al. profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Krys J. Kochut United States	17	881	666	510	495	225	51	1.5k
Motoshi Saeki Japan	18	1.0k 1.2×	692 1.0×	172 0.3×	197 0.4×	641 2.8×	108	2.1k
Marek Sergot United Kingdom	22	318 0.4×	1.5k 2.3×	216 0.4×	236 0.5×	132 0.6×	74	2.0k
Jérôme Euzenat France	15	1.4k 1.6×	2.4k 3.5×	495 1.0×	201 0.4×	934 4.2×	66	2.9k
Paolo Missier United Kingdom	26	1.3k 1.5×	550 0.8×	1.1k 2.1×	142 0.3×	185 0.8×	142	2.3k
Jesualdo Tomás Fernández‐Breis Spain	25	521 0.6×	931 1.4×	115 0.2×	141 0.3×	601 2.7×	125	1.6k
York Sure Germany	23	1.0k 1.2×	1.3k 2.0×	396 0.8×	293 0.6×	243 1.1×	60	1.7k
Michael Sintek Germany	19	923 1.0×	1.2k 1.8×	767 1.5×	263 0.5×	171 0.8×	55	2.1k
Marc Ehrig Germany	15	705 0.8×	766 1.2×	290 0.6×	218 0.4×	187 0.8×	23	1.0k
Adam Farquhar United States	18	697 0.8×	1.1k 1.7×	403 0.8×	159 0.3×	225 1.0×	49	1.5k
Ming Fan China	19	516 0.6×	331 0.5×	538 1.1×	71 0.1×	195 0.9×	120	1.6k

Countries citing papers authored by Krys J. Kochut

Since Specialization

Citations

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

Fields of papers citing papers by Krys J. Kochut

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Krys J. Kochut. 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 Krys J. Kochut. The network helps show where Krys J. Kochut may publish in the future.

Co-authorship network of co-authors of Krys J. Kochut

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

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

1.

Allahyari, Mehdi, Seyedamin Pouriyeh, & Krys J. Kochut. (2019). Combining semantic graph and probabilistic topic models for discovering coherent topics. 17(4). 365–379. 2 indexed citations

2.

Pouriyeh, Seyedamin, et al.. (2019). R-LDA: Profiling RDF Datasets Using Knowledge-Based Topic Modeling. UNICA IRIS Institutional Research Information System (University of Cagliari). 146–149. 4 indexed citations

3.

Allahyari, Mehdi, et al.. (2017). A Knowledge-based Topic Modeling Approach for Automatic Topic Labeling. International Journal of Advanced Computer Science and Applications. 8(9). 13 indexed citations

4.

Ranzinger, René, et al.. (2016). GLYDE-II: The GLYcan data exchange format. Perspectives in Science. 11. 24–30. 4 indexed citations

5.

Allahyari, Mehdi & Krys J. Kochut. (2015). Automatic Topic Labeling Using Ontology-Based Topic Models. 259–264. 24 indexed citations

6.

Miller, John A., et al.. (2015). Directions for Big Data Graph Analytics Research. 2(1). 15–27. 1 indexed citations

7.

Miller, John A., et al.. (2015). Research Directions for Big Data Graph Analytics. 785–794. 5 indexed citations

8.

Miller, John A., Amit Sheth, & Krys J. Kochut. (2014). Perspectives in Modeling: Simulation, Database, and Workflow. Journal of Bioresource Management.

9.

Allahyari, Mehdi, Krys J. Kochut, & Maciej Janik. (2014). Ontology-Based Text Classification into Dynamically Defined Topics. 273–278. 29 indexed citations

10.

Kochut, Krys J., John A. Miller, René Ranzinger, et al.. (2014). Qrator: A web-based curation tool for glycan structures. Glycobiology. 25(1). 66–73. 9 indexed citations

11.

McSkimming, Daniel, Eric Talevich, Samiksha Katiyar, et al.. (2014). ProKinO: A Unified Resource for Mining the Cancer Kinome. Human Mutation. 36(2). 175–186. 39 indexed citations

12.

Arpinar, I. Budak, et al.. (2014). CrowdLink: Crowdsourcing for Large-Scale Linked Data Management. 227–234. 1 indexed citations

13.

Kochut, Krys J., et al.. (2013). An Ontology-Aided Process Constraint Modeling Framework for Workflow Systems. 178–183. 1 indexed citations

14.

Kochut, Krys J., et al.. (2011). ProKinO: An Ontology for Integrative Analysis of Protein Kinases in Cancer. PLoS ONE. 6(12). e28782–e28782. 28 indexed citations

15.

Kochut, Krys J., et al.. (2004). Towards Efficient Integration of Complex Web Services Using a Unified Model for Protocol and Process.. International Conference on Internet Computing. 467–474. 1 indexed citations

16.

Miller, John A., et al.. (1998). WebWork: METEOR₂'s Web-based Workflow Management System. Journal of Bioresource Management. 77 indexed citations

17.

Prade, Rolf A., James W. Griffith, Krys J. Kochut, Jonathan Arnold, & William E. Timberlake. (1997). In vitro reconstruction of the Aspergillus (= Emericella ) nidulans genome. Proceedings of the National Academy of Sciences. 94(26). 14564–14569. 47 indexed citations

18.

Sheth, Amit, et al.. (1996). Supporting State-Wide Immunisation Tracking Using Multi-Paradigm Workflow Technology. Very Large Data Bases. 263–273. 26 indexed citations

19.

Miller, John A., et al.. (1995). Simulation modeling within workflow technology. 612–619. 16 indexed citations

20.

Miller, John A., et al.. (1990). Model Instantiation For Query Driven Simulation In Active KDL. Annual Simulation Symposium. 20(4). 15–32. 12 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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