Catherine Havasi

7.2k total citations · 3 hit papers
39 papers, 4.1k citations indexed

About

Catherine Havasi is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Computational Theory and Mathematics. According to data from OpenAlex, Catherine Havasi has authored 39 papers receiving a total of 4.1k indexed citations (citations by other indexed papers that have themselves been cited), including 33 papers in Artificial Intelligence, 6 papers in Computer Vision and Pattern Recognition and 6 papers in Computational Theory and Mathematics. Recurrent topics in Catherine Havasi's work include Topic Modeling (18 papers), Advanced Text Analysis Techniques (12 papers) and Semantic Web and Ontologies (11 papers). Catherine Havasi is often cited by papers focused on Topic Modeling (18 papers), Advanced Text Analysis Techniques (12 papers) and Semantic Web and Ontologies (11 papers). Catherine Havasi collaborates with scholars based in United States, United Kingdom and Singapore. Catherine Havasi's co-authors include Robert E. Speer, Erik Cambria, Björn W. Schuller, Yunqing Xia, Amir Hussain, Henry Lieberman, Karthik Dinakar, Rosalind W. Picard, James Pustejovsky and Haixun Wang and has published in prestigious journals such as Developmental Psychology, Multimedia Tools and Applications and IEEE Intelligent Systems.

In The Last Decade

Catherine Havasi

38 papers receiving 3.8k citations

Hit Papers

ConceptNet 5.5: An Open Multilingual Graph of General Kno... 2013 2026 2017 2021 2017 2013 2016 400 800 1.2k

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Catherine Havasi United States 18 3.4k 654 589 364 311 39 4.1k
Giuseppe Carenini Canada 34 2.5k 0.7× 867 1.3× 507 0.9× 375 1.0× 150 0.5× 174 3.6k
Alexander Gelbukh Mexico 29 4.5k 1.3× 497 0.8× 974 1.7× 503 1.4× 404 1.3× 312 5.7k
Asif Ekbal India 36 4.4k 1.3× 624 1.0× 735 1.2× 422 1.2× 348 1.1× 360 5.3k
Philip Resnik United States 40 5.6k 1.7× 472 0.7× 784 1.3× 292 0.8× 538 1.7× 158 7.1k
Andrea Esuli Italy 23 4.5k 1.3× 403 0.6× 1.2k 2.0× 557 1.5× 220 0.7× 80 5.3k
Ewan Klein United Kingdom 24 3.6k 1.1× 372 0.6× 624 1.1× 351 1.0× 250 0.8× 92 5.7k
David McClosky United States 18 4.8k 1.4× 697 1.1× 967 1.6× 346 1.0× 127 0.4× 26 5.9k
Timothy Baldwin Australia 37 4.6k 1.4× 384 0.6× 724 1.2× 299 0.8× 110 0.4× 262 5.4k
Marie‐Francine Moens Belgium 36 3.8k 1.1× 783 1.2× 1.1k 1.9× 348 1.0× 106 0.3× 280 5.2k
Michael Gamon United States 33 3.1k 0.9× 224 0.3× 704 1.2× 324 0.9× 441 1.4× 85 3.9k

Countries citing papers authored by Catherine Havasi

Since Specialization
Citations

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

Fields of papers citing papers by Catherine Havasi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Catherine Havasi. 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 Catherine Havasi. The network helps show where Catherine Havasi may publish in the future.

Co-authorship network of co-authors of Catherine Havasi

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

All Works

20 of 20 papers shown
1.
Cambria, Erik, Björn W. Schuller, Bing Liu, Haixun Wang, & Catherine Havasi. (2013). Knowledge-Based Approaches to Concept-Level Sentiment Analysis. IEEE Intelligent Systems. 28(2). 12–14. 97 indexed citations
2.
Speer, Robert E. & Catherine Havasi. (2012). Representing General Relational Knowledge in ConceptNet 5. Language Resources and Evaluation. 3679–3686. 223 indexed citations
3.
Dinakar, Karthik, et al.. (2012). Common Sense Reasoning for Detection, Prevention, and Mitigation of Cyberbullying. ACM Transactions on Interactive Intelligent Systems. 2(3). 1–30. 276 indexed citations
4.
Havasi, Catherine, et al.. (2012). The Glass Infrastructure — Using Common Sense to Create a Dynamic, Place‐Based Social‐Information System. AI Magazine. 33(2). 91–102. 1 indexed citations
5.
Havasi, Catherine, et al.. (2011). Comparing Matrix Decomposition Methods for Meta-Analysis and Reconstruction of Cognitive Neuroscience Results. The Florida AI Research Society. 6 indexed citations
6.
Havasi, Catherine, Richard Borovoy, Henry Holtzman, et al.. (2011). The Glass Infrastructure: Using Common Sense to Create a Dynamic, Place-Based Social Information System. Proceedings of the AAAI Conference on Artificial Intelligence. 25(2). 1589–1596. 2 indexed citations
7.
Havasi, Catherine, et al.. (2010). Open mind common sense: crowd-sourcing for common sense. National Conference on Artificial Intelligence. 53–53. 7 indexed citations
8.
Havasi, Catherine, Doug Lenat, & Benjamin Van Durme. (2010). Commonsense knowledge : papers from the AAAI Fall Symposium. 4 indexed citations
9.
Arnold, Kenneth C., et al.. (2010). Envisioning a robust, scalable metacognitive architecture built on dimensionality reduction. National Conference on Artificial Intelligence. 2–5. 3 indexed citations
10.
Cambria, Erik, Robert E. Speer, Catherine Havasi, & Amir Hussain. (2010). SenticNet: A Publicly Available Semantic Resource for Opinion Mining. Stirling Online Research Repository (University of Stirling). 14–18. 180 indexed citations
11.
Havasi, Catherine, et al.. (2010). Reducing the dimensionality of data streams using common sense. National Conference on Artificial Intelligence. 16–21. 1 indexed citations
12.
Speer, Robert E., et al.. (2010). Visualizing common sense connections with Luminoso. 9–12. 2 indexed citations
13.
Cambria, Erik, Amir Hussain, T.S. Durrani, et al.. (2010). Sentic Computing for patient centered applications. Research Output (Edinburgh Napier University). 1279–1282. 90 indexed citations
14.
Cambria, Erik, Amir Hussain, Catherine Havasi, Chris Eckl, & James B. Munro. (2010). Towards Crowd Validation of the UK National Health Service. 25 indexed citations
15.
Speer, Robert E., Catherine Havasi, & Henry Lieberman. (2008). AnalogySpace: reducing the dimensionality of common sense knowledge. National Conference on Artificial Intelligence. 548–553. 89 indexed citations
16.
Havasi, Catherine, James Pustejovsky, & Marc Verhagen. (2006). BULB: A Unified Lexical Browser.. Language Resources and Evaluation. 2253–2258. 2 indexed citations
17.
Rumshisky, Anna, Patrick Hanks, Catherine Havasi, & James Pustejovsky. (2006). Constructing a Corpus-based Ontology Using Model Bias.. The Florida AI Research Society. 24(4). 327–332. 17 indexed citations
18.
Pustejovsky, James, et al.. (2006). Towards a Generative Lexical Resource: The Brandeis Semantic Ontology.. Language Resources and Evaluation. 1702–1705. 40 indexed citations
19.
Wellner, Ben, James Pustejovsky, Catherine Havasi, Anna Rumshisky, & R. Supyan Sauri. (2006). Classification of discourse coherence relations. 117–117. 44 indexed citations
20.
Havasi, Catherine & Jesse Snedeker. (2004). The Adaptability of Language Specific Verb Lexicalization Biases. eScholarship (California Digital Library). 26(26). 6 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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