Tim O’Gorman

626 total citations
25 papers, 329 citations indexed

About

Tim O’Gorman is a scholar working on Artificial Intelligence, Materials Chemistry and Molecular Biology. According to data from OpenAlex, Tim O’Gorman has authored 25 papers receiving a total of 329 indexed citations (citations by other indexed papers that have themselves been cited), including 23 papers in Artificial Intelligence, 2 papers in Materials Chemistry and 1 paper in Molecular Biology. Recurrent topics in Tim O’Gorman's work include Natural Language Processing Techniques (22 papers), Topic Modeling (21 papers) and Semantic Web and Ontologies (7 papers). Tim O’Gorman is often cited by papers focused on Natural Language Processing Techniques (22 papers), Topic Modeling (21 papers) and Semantic Web and Ontologies (7 papers). Tim O’Gorman collaborates with scholars based in United States, Czechia and Norway. Tim O’Gorman's co-authors include Martha Palmer, Nathan Schneider, Jan Hajič, Nianwen Xue, Daniel Hershcovich, Stephan Oepen, Omri Abend, Milan Straka, Heng Ji and Ulf Hermjakob and has published in prestigious journals such as Language Resources and Evaluation, International Journal of Speech Technology and KI - Künstliche Intelligenz.

In The Last Decade

Tim O’Gorman

24 papers receiving 298 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Tim O’Gorman United States	11	316	34	26	23	21	25	329
Daniele Pighin Italy	11	380 1.2×	26 0.8×	26 1.0×	13 0.6×	57 2.7×	32	397
Vladimir Eidelman United States	9	444 1.4×	45 1.3×	42 1.6×	10 0.4×	32 1.5×	15	465
Diganta Saha India	8	307 1.0×	21 0.6×	18 0.7×	8 0.3×	28 1.3×	29	335
Altaf Rahman United States	9	270 0.9×	21 0.6×	31 1.2×	17 0.7×	25 1.2×	11	283
Patrick Xia United States	9	264 0.8×	60 1.8×	14 0.5×	7 0.3×	24 1.1×	14	284
Alok Ranjan Pal India	7	285 0.9×	17 0.5×	19 0.7×	7 0.3×	25 1.2×	26	308
Claudio Delli Bovi Italy	9	309 1.0×	21 0.6×	22 0.8×	13 0.6×	10 0.5×	14	316
David Burkett United States	8	298 0.9×	25 0.7×	18 0.7×	8 0.3×	31 1.5×	13	311
Weiguang Qu China	8	209 0.7×	21 0.6×	9 0.3×	10 0.4×	43 2.0×	36	227
Naveen Arivazhagan United States	3	214 0.7×	55 1.6×	9 0.3×	6 0.3×	28 1.3×	4	249

Countries citing papers authored by Tim O’Gorman

Since Specialization

Citations

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

Fields of papers citing papers by Tim O’Gorman

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Tim O’Gorman. 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 Tim O’Gorman. The network helps show where Tim O’Gorman may publish in the future.

Co-authorship network of co-authors of Tim O’Gorman

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

All Works

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20 of 20 papers shown

O’Gorman, Tim, et al.. (2022). DISAPERE: A Dataset for Discourse Structure in Peer Review Discussions. Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies. 1234–1249. 6 indexed citations

Naseem, Tahira, Tim O’Gorman, Young‐Suk Lee, et al.. (2022). DocAMR: Multi-Sentence AMR Representation and Evaluation. Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies. 3496–3505. 5 indexed citations

Lai, Kenneth, Tim O’Gorman, Andrew Cowell, et al.. (2021). Designing a Uniform Meaning Representation for Natural Language Processing. KI - Künstliche Intelligenz. 35(3-4). 343–360. 16 indexed citations

Drozdov, Andrew, et al.. (2021). Improved Latent Tree Induction with Distant Supervision via Span Constraints. Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing. 4818–4831. 3 indexed citations

Cowell, Andrew, et al.. (2021). Theoretical and Practical Issues in the Semantic Annotation of Four Indigenous Languages. 12–22.

Oepen, Stephan, Omri Abend, Lasha Abzianidze, et al.. (2020). MRP 2020: The Second Shared Task on Cross-Framework and Cross-Lingual Meaning Representation Parsing. Research at the University of Copenhagen (University of Copenhagen). 1–22. 31 indexed citations

Mysore, Sheshera, et al.. (2020). An Instance Level Approach for Shallow Semantic Parsing in Scientific Procedural Text. 3010–3017. 1 indexed citations

O’Gorman, Tim, et al.. (2020). Cross-lingual annotation: a road map for low-and no-resource languages. 30–40. 2 indexed citations

O’Gorman, Tim, et al.. (2018). The New Propbank: Aligning Propbank with AMR through POS Unification. Language Resources and Evaluation. 6 indexed citations

10.

O’Gorman, Tim, et al.. (2018). AMR Beyond the Sentence: the Multi-sentence AMR corpus. International Conference on Computational Linguistics. 3693–3702. 22 indexed citations

11.

Bonial, Claire, Kira Griffitt, Ulf Hermjakob, et al.. (2018). Abstract Meaning Representation of Constructions: The More We Include, the Better the Representation.. Language Resources and Evaluation. 6 indexed citations

12.

Hwang, Jena D., Archna Bhatia, Na-Rae Han, et al.. (2017). Double Trouble: The Problem of Construal in Semantic Annotation of Adpositions. 178–188. 8 indexed citations

13.

O’Gorman, Tim, et al.. (2016). Richer Event Description: Integrating event coreference with temporal, causal and bridging annotation. 47–56. 73 indexed citations

14.

Hong, Yu, et al.. (2016). Building a Cross-document Event-Event Relation Corpus. 1–6. 16 indexed citations

15.

Bies, Ann, Zhiyi Song, Joe Ellis, et al.. (2016). A Comparison of Event Representations in DEFT. 27–36. 10 indexed citations

16.

Zaghouani, Wajdi, et al.. (2015). AMPN: a semantic resource for Arabic morphological patterns. International Journal of Speech Technology. 19(2). 281–288. 1 indexed citations

17.

Schneider, Nathan, Jeffrey Flanigan, & Tim O’Gorman. (2015). The Logic of AMR: Practical, Unified, Graph-Based Sentence Semantics for NLP. Edinburgh Research Explorer. 4–5. 2 indexed citations

18.

Styler, Will, et al.. (2014). Challenges of Adding Causation to Richer Event Descriptions. 12–20. 19 indexed citations

19.

Hawwari, Abdelati, et al.. (2013). Building a lexical semantic resource for Arabic morphological Patterns. 23. 1–6. 6 indexed citations

20.

O’Gorman, Tim. (2003). Fort Lee, Virginia. 1 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.

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