Stephen Dill

1.0k total citations
15 papers, 623 citations indexed

About

Stephen Dill is a scholar working on Information Systems, Artificial Intelligence and Statistical and Nonlinear Physics. According to data from OpenAlex, Stephen Dill has authored 15 papers receiving a total of 623 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Information Systems, 6 papers in Artificial Intelligence and 4 papers in Statistical and Nonlinear Physics. Recurrent topics in Stephen Dill's work include Semantic Web and Ontologies (4 papers), Complex Network Analysis Techniques (4 papers) and Data Quality and Management (4 papers). Stephen Dill is often cited by papers focused on Semantic Web and Ontologies (4 papers), Complex Network Analysis Techniques (4 papers) and Data Quality and Management (4 papers). Stephen Dill collaborates with scholars based in United States, India and Argentina. Stephen Dill's co-authors include Andrew Tomkins, Sridhar Rajagopalan, Daniel Gruhl, David Gibson, John A. Tomlin, Jason Y. Zien, Anant Jhingran, Tapas Kanungo, Nadav Eiron and R. Guha and has published in prestigious journals such as Journal of Web Semantics, ACM Transactions on Internet Technology and Very Large Data Bases.

In The Last Decade

Stephen Dill

15 papers receiving 535 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Stephen Dill United States	9	384	383	154	90	84	15	623
L. Venkata Subramaniam India	15	460 1.2×	226 0.6×	84 0.5×	110 1.2×	54 0.6×	60	711
Nadav Eiron United States	11	550 1.4×	587 1.5×	170 1.1×	105 1.2×	106 1.3×	17	883
Giuseppe Pirrò Italy	12	446 1.2×	182 0.5×	160 1.0×	66 0.7×	63 0.8×	49	578
Sergej Sizov Germany	11	278 0.7×	212 0.6×	92 0.6×	58 0.6×	47 0.6×	43	502
Jeffrey Pound Canada	12	346 0.9×	255 0.7×	106 0.7×	50 0.6×	113 1.3×	21	516
Isaac G. Councill United States	13	504 1.3×	267 0.7×	91 0.6×	67 0.7×	139 1.7×	25	704
Byron J. Gao United States	12	284 0.7×	198 0.5×	96 0.6×	61 0.7×	52 0.6×	46	479
Robert Jäschke Germany	14	374 1.0×	507 1.3×	138 0.9×	152 1.7×	29 0.3×	47	750
Tanveer A. Faruquie India	15	340 0.9×	183 0.5×	93 0.6×	97 1.1×	52 0.6×	47	585
Uldis Bojārs Ireland	11	291 0.8×	248 0.6×	100 0.6×	52 0.6×	41 0.5×	27	435

Countries citing papers authored by Stephen Dill

Since Specialization

Citations

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

Fields of papers citing papers by Stephen Dill

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Stephen Dill

This figure shows the co-authorship network connecting the top 25 collaborators of Stephen Dill. A scholar is included among the top collaborators of Stephen Dill 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 Stephen Dill. Stephen Dill 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:

15 of 15 papers shown

1.

Liu, Haibin, et al.. (2014). A Machine Learning Approach to Combining Individual Strength and Team Features for Team Recommendation. 213–218. 11 indexed citations

2.

Ajmera, Jitendra, et al.. (2013). A CRM system for Social Media. 3 indexed citations

3.

Dill, Stephen, et al.. (2013). The Work Exchange: Peer-to-Peer Enterprise Crowdsourcing. Proceedings of the AAAI Conference on Human Computation and Crowdsourcing. 1. 89–90. 2 indexed citations

4.

Ajmera, Jitendra, et al.. (2013). A CRM system for social media. 49–58. 12 indexed citations

5.

Moitra, Abha, et al.. (2010). Addressing uncertainty and conflicts in cross-domain data provenance. 141 1 2. 912–917. 1 indexed citations

6.

Moitra, Abha, et al.. (2009). Data Provenance architecture to support Information Assurance in a Multi-Level Secure Environment. 3188. 1–7. 6 indexed citations

7.

Dill, Stephen, et al.. (2009). Team analytics. 83–86. 5 indexed citations

8.

Tang, John, et al.. (2009). Global differences in attributes of email usage. 185–194. 13 indexed citations

9.

Gruhl, Daniel, et al.. (2006). The web beyond popularity. 183–192. 12 indexed citations

10.

Dill, Stephen, Nadav Eiron, David Gibson, et al.. (2003). A Case for Automated Large Scale Semantic Annotation. SSRN Electronic Journal. 1 indexed citations

11.

Dill, Stephen, John A. Tomlin, Jason Y. Zien, et al.. (2003). SemTag and seeker. 55 indexed citations

12.

Dill, Stephen, John A. Tomlin, Jason Y. Zien, et al.. (2003). SemTag and seeker. 178–178. 282 indexed citations

13.

Dill, Stephen, Nadav Eiron, David Gibson, et al.. (2003). A case for automated large-scale semantic annotation. Journal of Web Semantics. 1(1). 115–132. 75 indexed citations

14.

Dill, Stephen, Ravi Kumar, Kevin S. McCurley, et al.. (2002). Self-similarity in the web. ACM Transactions on Internet Technology. 2(3). 205–223. 107 indexed citations

15.

Dill, Stephen, Ravi Kumar, Kevin S. McCurley, et al.. (2001). Self-similarity in the Web. Very Large Data Bases. 69–78. 38 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.

Explore authors with similar magnitude of impact