Thomas Lin
Impact in
- Artificial Intelligence top 2%
- Topic Modeling
- Natural Language Processing Techniques
- Semantic Web and Ontologies
- Advanced Text Analysis Techniques
- Speech and dialogue systems
- Health Informatics top 10%
Papers in
-
- Topic Modeling 14
- Natural Language Processing Techniques 10
- Semantic Web and Ontologies 4
- Machine Learning in Healthcare 2
-
- Biomedical Text Mining and Ontologies 5
- Co-authors
- Oren Etzioni (6 shared papers)Grace Lim (1 shared paper)Push Singh (1 shared paper)Erik T. Mueller (1 shared paper)Michael Gamon (2 shared papers)Patrick Pantel (2 shared papers)Asma Ben Abacha (4 shared papers)Wen-wai Yim (3 shared papers)
- Journals
- NeuroImage (1 paper)Scientific Data (1 paper)Lecture notes in computer science (1 paper)National Conference on Artificial Intelligence (2 papers)Empirical Methods in Natural Language Processing (2 papers)
- Partner nations
- United StatesAustriaUnited Kingdom
In The Last Decade
Thomas Lin
18 papers receiving 724 citations
Peers
Comparison fields: 5 of 72
- Artificial Intelligence 647
- Health Informatics 15
- Computer Science Applications 46
- Information Systems 156
- Management Science and Operations Research 75
Countries citing papers authored by Thomas Lin
This map shows the geographic impact of Thomas Lin'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 Lin with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Thomas Lin more than expected).
Fields of papers citing papers by Thomas Lin
This network shows the impact of papers produced by Thomas Lin. 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 Lin. The network helps show where Thomas Lin may publish in the future.
Co-authors
The 25 scholars most cited alongside Thomas Lin, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2002 | 328 | |
| 2 | Entity Linking at Web Scale | 2012 | 67 |
| 3 | No Noun Phrase Left Behind: Detecting and Typing Unlinkable Entities | 2012 | 66 |
| 4 | 2012 | 66 | |
| 5 | 2020 | 41 | |
| 6 | Mining Entity Types from Query Logs via User Intent Modeling | 2012 | 36 |
| 7 | 2023 | 30 | |
| 8 | 2023 | 30 | |
| 9 | Identifying Functional Relations in Web Text | 2010 | 26 |
| 10 | Machine Reading at the University of Washington | 2010 | 23 |
| 11 | 2012 | 21 | |
| 12 | 2022 | 17 | |
| 13 | 2009 | 15 | |
| 14 | 2023 | 6 | |
| 15 | 2002 | 4 | |
| 16 | 2025 | 3 | |
| 17 | Commonsense from the Web: Relation Properties | 2010 | 3 |
| 18 | 2001 | 2 |
About Thomas Lin
Thomas Lin is a scholar working on Artificial Intelligence, Molecular Biology, Information Systems, Health Information Management and Communication, having authored 18 papers that have together received 784 indexed citations. Recurring topics across this work include Topic Modeling (14 papers), Natural Language Processing Techniques (10 papers), Biomedical Text Mining and Ontologies (5 papers), Semantic Web and Ontologies (4 papers), Web Data Mining and Analysis (3 papers), Information Retrieval and Search Behavior (3 papers), Machine Learning in Healthcare (2 papers) and Electronic Health Records Systems (2 papers). The work is most often cited by research in Artificial Intelligence (647 citations), Health Informatics (15 citations), Computer Science Applications (46 citations), Information Systems (156 citations) and Management Science and Operations Research (75 citations). Thomas Lin has collaborated with scholars based in United States, Austria and United Kingdom. Frequent co-authors include Oren Etzioni, Grace Lim, Push Singh, Erik T. Mueller, Michael Gamon, Patrick Pantel, Asma Ben Abacha, Wen-wai Yim, Anitha Kannan and Ariel Fuxman. Their work appears in journals such as NeuroImage, Scientific Data, Lecture notes in computer science, National Conference on Artificial Intelligence and Empirical Methods in Natural Language Processing.
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.