Thomas R. Lynam

1.2k total citations
19 papers, 800 citations indexed

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 19 papers receiving a total of 800 indexed citations (citations by other indexed papers that have themselves been cited), including 18 papers in Artificial Intelligence, 12 papers in Information Systems and 3 papers in Computer Networks and Communications. Recurrent topics in Thomas R. Lynam's work include Topic Modeling (11 papers), Natural Language Processing Techniques (8 papers) and Text and Document Classification Technologies (6 papers). Thomas R. Lynam is often cited by papers focused on Topic Modeling (11 papers), Natural Language Processing Techniques (8 papers) and Text and Document Classification Technologies (6 papers). Thomas R. Lynam collaborates with scholars based in Canada and United States. Thomas R. Lynam's co-authors include Gordon V. Cormack, Charles L. A. Clarke, Bogdan Filipič, Blaž Zupan, Egidio L. Terra, David R. Cheriton, Michael Laszlo, Chris Buckley, David L. Yeung and Donna Harman and has published in prestigious journals such as Journal of Machine Learning Research, ACM Transactions on Information Systems and Information Retrieval.

In The Last Decade

Thomas R. Lynam

19 papers receiving 688 citations

Peers

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).

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.

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

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

All Works

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19 of 19 papers shown

#	Work	Indexed citations
1	Swapping documents and terms 2009 ·Information Retrieval ·Charles L. A. Clarke, Gordon V. Cormack, Thomas R. Lynam, Chris Buckley, Donna Harman	5
2	MultiText Legal Experiments at TREC 2008. 2008 ·Text REtrieval Conference ·Thomas R. Lynam, Gordon V. Cormack	2
3	Validity and power of t-test for comparing MAP and GMAP 2007 ·Gordon V. Cormack, Thomas R. Lynam	18
4	Power and bias of subset pooling strategies 2007 ·Gordon V. Cormack, Thomas R. Lynam	17
5	Online supervised spam filter evaluation 2007 ·ACM Transactions on Information Systems ·Gordon V. Cormack, Thomas R. Lynam	74
6	Spam Filtering Using Statistical Data Compression Models 2006 ·Journal of Machine Learning Research ·(unknown), Bogdan Filipič, Gordon V. Cormack, Thomas R. Lynam, Blaž Zupan	181
7	Statistical precision of information retrieval evaluation 2006 ·Gordon V. Cormack, Thomas R. Lynam	70
8	On-line spam filter fusion 2006 ·Thomas R. Lynam, Gordon V. Cormack, David R. Cheriton	34
9	Spam Corpus Creation for TREC. 2005 ·Gordon V. Cormack, Thomas R. Lynam	57
10	A Study of Supervised Spam Detection applied to Eight Months of Personal E-Mail 2004 ·Gordon V. Cormack, Thomas R. Lynam	6
11	A multi-system analysis of document and term selection for blind feedback 2004 ·Thomas R. Lynam, Chris Buckley, Charles L. A. Clarke, Gordon V. Cormack	17
12	Task-Specific Query Expansion (MultiText Experiments for TREC 2003). 2003 ·Text REtrieval Conference ·David L. Yeung, Charles L. A. Clarke, Gordon V. Cormack, Thomas R. Lynam, Egidio L. Terra	16
13	Statistical Selection of Exact Answers (MultiText Experiments for TREC 2002). 2002 ·Text REtrieval Conference ·Charles L. A. Clarke, Gordon V. Cormack, (unknown), Michael Laszlo, Thomas R. Lynam, Egidio L. Terra, (unknown)	31
14	The impact of corpus size on question answering performance 2002 ·Charles L. A. Clarke, Gordon V. Cormack, Michael Laszlo, Thomas R. Lynam, Egidio L. Terra	22
15	The impact of corpus size on question answering performance 2002 ·(unknown), Gordon V. Cormack, Michael Laszlo, Thomas R. Lynam, Egidio L. Terra	2
16	Web Reinforced Question Answering (MultiTest Experiments for TREC 2001). 2001 ·Text REtrieval Conference ·Charles L. A. Clarke, Gordon V. Cormack, Thomas R. Lynam, (unknown), (unknown)	25
17	Information extraction with term frequencies 2001 ·Thomas R. Lynam, (unknown), Gordon V. Cormack	5
18	Exploiting redundancy in question answering 2001 ·Charles L. A. Clarke, Gordon V. Cormack, Thomas R. Lynam	167
19	Question Answering by Passage Selection (MultiText Experiments for TREC-9). 2000 ·Text REtrieval Conference ·Charles L. A. Clarke, Gordon V. Cormack, (unknown), Thomas R. Lynam	51

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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