Ted E. Senator

2.4k total citations · 1 hit paper
23 papers, 1.5k citations indexed

About

Ted E. Senator is a scholar working on Artificial Intelligence, Computer Networks and Communications and Information Systems. According to data from OpenAlex, Ted E. Senator has authored 23 papers receiving a total of 1.5k indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Artificial Intelligence, 8 papers in Computer Networks and Communications and 8 papers in Information Systems. Recurrent topics in Ted E. Senator's work include Data Mining Algorithms and Applications (7 papers), Network Security and Intrusion Detection (6 papers) and Anomaly Detection Techniques and Applications (6 papers). Ted E. Senator is often cited by papers focused on Data Mining Algorithms and Applications (7 papers), Network Security and Intrusion Detection (6 papers) and Anomaly Detection Techniques and Applications (6 papers). Ted E. Senator collaborates with scholars based in United States. Ted E. Senator's co-authors include Tim Finin, Robert Neches, Ramesh S. Patil, William Swartout, Richard Fikes, Tom Gruber, Pedro Domingos, Lise Getoor, Christos Faloutsos and Henry G. Goldberg and has published in prestigious journals such as Communications of the ACM, Artificial Intelligence and AI Magazine.

In The Last Decade

Ted E. Senator

19 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.

Enabling technology for knowledge sharing

1991 780 citations Robert Neches, Richard Fikes et al. AI Magazine profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Ted E. Senator United States	12	868	528	343	206	152	23	1.5k
Alexandre Passant Ireland	21	851 1.0×	669 1.3×	346 1.0×	170 0.8×	100 0.7×	73	1.5k
Domenico Ursino Italy	24	794 0.9×	610 1.2×	619 1.8×	268 1.3×	169 1.1×	152	1.6k
Fabien Gandon France	15	642 0.7×	426 0.8×	204 0.6×	146 0.7×	85 0.6×	79	1.1k
Giuseppe Manco Italy	19	592 0.7×	526 1.0×	255 0.7×	440 2.1×	170 1.1×	95	1.5k
David B. Skillicorn Canada	25	882 1.0×	509 1.0×	805 2.3×	174 0.8×	157 1.0×	166	2.2k
Yuanzhuo Wang China	22	1.1k 1.3×	408 0.8×	282 0.8×	206 1.0×	105 0.7×	127	2.0k
Stephen Cranefield New Zealand	18	765 0.9×	470 0.9×	249 0.7×	65 0.3×	115 0.8×	116	1.2k
Giuseppe Fenza Italy	21	768 0.9×	487 0.9×	229 0.7×	63 0.3×	226 1.5×	88	1.5k
Li Ding United States	27	1.4k 1.7×	1.1k 2.0×	491 1.4×	266 1.3×	188 1.2×	103	2.4k
Athanasios Tsakalidis Greece	17	446 0.5×	478 0.9×	252 0.7×	75 0.4×	99 0.7×	111	1.2k

Countries citing papers authored by Ted E. Senator

Since Specialization

Citations

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

Fields of papers citing papers by Ted E. Senator

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ted E. Senator. 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 Ted E. Senator. The network helps show where Ted E. Senator may publish in the future.

Co-authorship network of co-authors of Ted E. Senator

This figure shows the co-authorship network connecting the top 25 collaborators of Ted E. Senator. A scholar is included among the top collaborators of Ted E. Senator 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 Ted E. Senator. Ted E. Senator 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.

Holder, Lawrence B., et al.. (2025). Introduction to open-world AI. Artificial Intelligence. 347. 104393–104393. 1 indexed citations

2.

Goldberg, Henry G., et al.. (2017). Insider Threat Detection in PRODIGAL. Proceedings of the ... Annual Hawaii International Conference on System Sciences. 14 indexed citations

3.

Goldberg, Henry G., et al.. (2016). Explaining and Aggregating Anomalies to Detect Insider Threats. 17. 2739–2748. 12 indexed citations

4.

Young, William T., et al.. (2014). Detecting Unknown Insider Threat Scenarios. 277–288. 27 indexed citations

5.

Goldberg, Henry G., et al.. (2013). Context-Aware Insider Threat Detection. National Conference on Artificial Intelligence. 5 indexed citations

6.

Young, William T., et al.. (2013). Use of Domain Knowledge to Detect Insider Threats in Computer Activities. 60–67. 30 indexed citations

7.

Ghani, Rayid, Ted E. Senator, Paul S. Bradley, et al.. (2013). Proceedings of the 19th ACM SIGKDD international conference on Knowledge discovery and data mining. 1 indexed citations

8.

Senator, Ted E., et al.. (2013). Distinguishing the unexplainable from the merely unusual. 40–45. 3 indexed citations

9.

Senator, Ted E.. (2006). Multi-Stage Classification. 386–393. 32 indexed citations

10.

Senator, Ted E.. (2005). Link mining applications. ACM SIGKDD Explorations Newsletter. 7(2). 76–83. 24 indexed citations

11.

Popp, Robert L., et al.. (2004). Countering terrorism through information technology. Communications of the ACM. 47(3). 36–43. 46 indexed citations

12.

Getoor, Lise, Ted E. Senator, Pedro Domingos, & Christos Faloutsos. (2003). Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining. Knowledge Discovery and Data Mining. 341 indexed citations

13.

Senator, Ted E. & Henry G. Goldberg. (2002). Industry: break detection systems. Oxford University Press eBooks. 863–873.

14.

Senator, Ted E., et al.. (2001). The NASD regulation advanced detection system: integrating data mining and visualization for break detection in the NASDAQ stock market. Morgan Kaufmann Publishers Inc. eBooks. 20(16). 363–371. 4 indexed citations

15.

Senator, Ted E.. (2000). Ongoing management and application of discovered knowledge in a large regulatory organization. 20. 44–53. 23 indexed citations

16.

Senator, Ted E., et al.. (1998). The NASD Regulation Advanced-Detection System (ADS). AI Magazine. 20(1). 1055–1062. 1 indexed citations

17.

Senator, Ted E., et al.. (1995). The FinCEN Artificial Intelligence System: Identifying Potential Money Laundering from Reports of Large Cash Transactions.. Innovative Applications of Artificial Intelligence. 156–170. 38 indexed citations

18.

Goldberg, Henry G. & Ted E. Senator. (1995). Restructuring Databases for knowledge discovery by consolidation and link formation. Knowledge Discovery and Data Mining. 136–141. 50 indexed citations

19.

Neches, Robert, Richard Fikes, Tim Finin, et al.. (1991). Enabling technology for knowledge sharing. AI Magazine. 12(3). 36–56. 780 indexed citations breakdown →

20.

Senator, Ted E., et al.. (1989). Naval Battle Management Decision Aiding.. Innovative Applications of Artificial Intelligence.

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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