Thomas R. Lynam

About

Thomas R. Lynam is a scholar working on Artificial Intelligence, Information Systems and Computer Networks and Communications. According to data from OpenAlex, Thomas R. Lynam has authored 11 papers receiving a total of 305 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Artificial Intelligence, 8 papers in Information Systems and 3 papers in Computer Networks and Communications. Recurrent topics in Thomas R. Lynam’s work include Topic Modeling (6 papers), Natural Language Processing Techniques (4 papers) and Spam and Phishing Detection (3 papers). Thomas R. Lynam is often cited by papers focused on Topic Modeling (6 papers), Natural Language Processing Techniques (4 papers) and Spam and Phishing Detection (3 papers). Thomas R. Lynam collaborates with scholars based in Canada and United States. Thomas R. Lynam's co-authors include Gordon V. Cormack, Blaž Zupan, Bogdan Filipič, Charles L. A. Clarke, Egidio L. Terra, Michael Laszlo, David L. Yeung, Chris Buckley and Donna Harman and has published in prestigious journals such as Journal of Machine Learning Research, Information Retrieval and CiteSeer X (The Pennsylvania State University).

In The Last Decade

Co-authorship network of co-authors of Thomas R. Lynam i

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Fields of papers citing papers by Thomas R. Lynam

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Thomas R. Lynam. 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 Thomas R. Lynam. The network helps show where Thomas R. Lynam may publish in the future.

Countries citing papers authored by Thomas R. Lynam

Since Specialization

Citations

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

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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