Raefer Gabriel

1.3k citations
5 papers · 209 · h-index 5

Impact in

    • Topic Modeling
    • Speech and dialogue systems
    • Natural Language Processing Techniques
    • AI in Service Interactions
    • Sentiment Analysis and Opinion Mining
    • Text Readability and Simplification

Papers in

    • Topic Modeling 4
    • AI in Service Interactions 3
    • Speech and dialogue systems 3
    • Advanced Text Analysis Techniques 1
    • Wikis in Education and Collaboration 1

Raefer Gabriel

5 papers receiving 195 citations

Peers

Raefer Gabriel
Comparison fields: 5 of 39
  • Artificial Intelligence 191
  • Health Informatics 6
  • Applied Psychology 6
  • Computer Vision and Pattern Recognition 22
  • Social Psychology 22
Replace Chandra Khatri with:
Chandra Khatri China
James Ryan United States
Farhad Bin Siddique Hong Kong
Weiyan Shi United States
Helena de Medeiros Caseli Brazil
Miruna Clinciu United Kingdom
Raquel Justo Spain
Pradyumna Tambwekar United States
Saffron Huang United Kingdom
Johnny Tian-Zheng Wei United States
Raefer Gabriel relative to Chandra Khatri China Chandra Khatri's profile →
Citations per field
00.5×4.4×
Chandra Khatri · 1×
Citations per year

Countries citing papers authored by Raefer Gabriel

Since Specialization
Citations

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

Fields of papers citing papers by Raefer Gabriel

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 18 scholars most cited alongside Raefer Gabriel, 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 Raefer Gabriel Line = papers co-authored together Raefer Gabriel links everyone, so they are left out of the graph.

All Works

5 of 5 papers shown
#Work
1 2019127
2 201837
3
On Evaluating and Comparing Conversational Agents
201824
4
Further advances in open domain dialog systems in the Third Alexa Prize Socialbot Grand Challenge
202012
5 20189

About Raefer Gabriel

Raefer Gabriel is a scholar working on Artificial Intelligence, Communication, Health Informatics, Infectious Diseases and Organic Chemistry, having authored 5 papers that have together received 209 indexed citations. Recurring topics across this work include Topic Modeling (4 papers), AI in Service Interactions (3 papers), Speech and dialogue systems (3 papers), Advanced Text Analysis Techniques (1 paper), Artificial Intelligence in Healthcare and Education (1 paper) and Wikis in Education and Collaboration (1 paper). The work is most often cited by research in Artificial Intelligence (191 citations), Health Informatics (6 citations), Applied Psychology (6 citations), Computer Vision and Pattern Recognition (22 citations) and Social Psychology (22 citations). Raefer Gabriel has collaborated with scholars based in China, Germany and United States. Frequent co-authors include Behnam Hedayatnia, Anu Venkatesh, Karthik Gopalakrishnan, Dilek Hakkani‐Tür, Chandra Khatri, Ashwin Ram, Rohit Prasad, Rahul Goel, Fenfei Guo and Arindam Mandal. Their work appears in journals such as AI Magazine and arXiv (Cornell University).

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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