Citations per year, relative to Emmett Tomai Emmett Tomai (= 1×)
peers
Yun‐Cheng Ju
Countries citing papers authored by Emmett Tomai
Since
Specialization
Citations
This map shows the geographic impact of Emmett Tomai'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 Emmett Tomai with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Emmett Tomai more than expected).
This network shows the impact of papers produced by Emmett Tomai. 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 Emmett Tomai. The network helps show where Emmett Tomai may publish in the future.
Co-authorship network of co-authors of Emmett Tomai
This figure shows the co-authorship network connecting the top 25 collaborators of Emmett Tomai.
A scholar is included among the top collaborators of Emmett Tomai 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 Emmett Tomai. Emmett Tomai is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Tomai, Emmett. (2018). Extraction of Interaction Events for Learning Reasonable Behavior in an Open-World Survival Game.. National Conference on Artificial Intelligence. 574–580.
Tomai, Emmett, et al.. (2014). Exploring Narrative Structure with MMORPG Quest Stories. Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment. 10(4). 35–37.2 indexed citations
6.
Tomai, Emmett, et al.. (2014). Adapting In-Game Agent Behavior by Observation of Players Using Learning Behavior Trees. ScholarWorks @ UTRGV (The University of Texas Rio Grande Valley).5 indexed citations
Tomai, Emmett & Kenneth D. Forbus. (2009). EA NLU: Practical Language Understanding for Cognitive Modeling. The Florida AI Research Society. 117–122.24 indexed citations
12.
Forbus, Kenneth D., Kate Lockwood, Abhishek Sharma, & Emmett Tomai. (2009). Steps towards a second generation learning by Reading system. National Conference on Artificial Intelligence. 36–43.3 indexed citations
Tomai, Emmett & Ken Forbus. (2008). Using Qualitative Reasoning for the Attribution of Moral Responsibility. eScholarship (California Digital Library). 30(30).4 indexed citations
15.
Tomai, Emmett & Kenneth D. Forbus. (2007). Narrative Presentation and Meaning. National Conference on Artificial Intelligence. 162–165.
16.
Forbus, Kenneth D., Andrew Lovett, Emmett Tomai, & Jeffrey Usher. (2005). A Structure Mapping Model for Solving Geometric Analogy Problems. eScholarship (California Digital Library). 27(27).6 indexed citations
17.
Forbus, Kenneth D., Jeffrey Usher, & Emmett Tomai. (2005). Analogical learning of visual/conceptual relationships in sketches. 202–208.8 indexed citations
18.
Klenk, Matthew, et al.. (2005). Solving everyday physical reasoning problems by analogy using sketches. 209–215.17 indexed citations
19.
Forbus, Kenneth D., Kate Lockwood, Matthew Klenk, Emmett Tomai, & Jeffrey Usher. (2004). Open-Domain Sketch Understanding: The nuSketch Approach.. National Conference on Artificial Intelligence. 58–63.18 indexed citations
20.
Forbus, Kenneth D., Emmett Tomai, & Jeffrey Usher. (2003). Qualitative Spatial Reasoning for Visual Grouping in Sketches. Defense Technical Information Center (DTIC).9 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.