Patrick W. Verga

811 citations
18 papers · 530 · h-index 10

Impact in

Papers in

    • Topic Modeling 14
    • Natural Language Processing Techniques 13
    • Semantic Web and Ontologies 3
    • Speech Recognition and Synthesis 2
    • Memory and Neural Mechanisms 3
    • Sleep and Wakefulness Research 3

Patrick W. Verga

18 papers receiving 513 citations

Peers

Patrick W. Verga
Comparison fields: 5 of 56
  • Behavioral Neuroscience 34
  • Artificial Intelligence 301
  • Experimental and Cognitive Psychology 110
  • Cognitive Neuroscience 149
  • Endocrine and Autonomic Systems 40
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Citations per field
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Citations per year

Countries citing papers authored by Patrick W. Verga

Since Specialization
Citations

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

Fields of papers citing papers by Patrick W. Verga

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Patrick W. Verga. 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 Patrick W. Verga. The network helps show where Patrick W. Verga may publish in the future.

Co-authors

The 25 scholars most cited alongside Patrick W. Verga, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Patrick W. Verga Line = papers co-authored together Patrick W. Verga links everyone, so they are left out of the graph.

All Works

18 of 18 papers shown
#Work
1 2012107
2 201374
3 201966
4 201860
5 201849
6 201833
7 201827
8 201726
9 201524
10 201618
11 20169
12 20139
13
Reasoning Over Virtual Knowledge Bases With Open Predicate Relations
20218
14 20197
15
Building Knowledge Bases with Universal Schema: Cold Start and Slot-Filling Approaches.
20155
16
Extracting Multilingual Relations under Limited Resources: TAC 2016 Cold-Start KB construction and Slot-Filling using Compositional Universal Schema.
20164
17 20172
18
UMass at TREC WEB 2014: Entity Query Feature Expansion using Knowledge Base Links
20142

About Patrick W. Verga

Patrick W. Verga is a scholar working on Artificial Intelligence, Cognitive Neuroscience, Endocrine and Autonomic Systems, Experimental and Cognitive Psychology and Molecular Biology, having authored 18 papers that have together received 530 indexed citations. Recurring topics across this work include Topic Modeling (14 papers), Natural Language Processing Techniques (13 papers), Biomedical Text Mining and Ontologies (5 papers), Memory and Neural Mechanisms (3 papers), Semantic Web and Ontologies (3 papers), Sleep and Wakefulness Research (3 papers), Sleep and related disorders (2 papers) and Speech Recognition and Synthesis (2 papers). The work is most often cited by research in Behavioral Neuroscience (34 citations), Artificial Intelligence (301 citations), Experimental and Cognitive Psychology (110 citations), Cognitive Neuroscience (149 citations) and Endocrine and Autonomic Systems (40 citations). Patrick W. Verga has collaborated with scholars based in United States, United Kingdom and Ukraine. Frequent co-authors include Andrew McCallum, Edward F. Pace‐Schott, Rebecca M. C. Spencer, Emma Strubell, Andrew Drozdov, Mohit Iyyer, Mohit Yadav, Scott P. Orr, Nathan Greenberg and Luke Vilnis. Their work appears in journals such as Theory and applications of categories, Journal of Psychiatric Research, Psychiatry Research, PLoS ONE and Text REtrieval Conference.

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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