Dan Gillick
Impact in
- Artificial Intelligence top 2%
- Topic Modeling
- Natural Language Processing Techniques
- Advanced Text Analysis Techniques
- Speech and dialogue systems
- Speech Recognition and Synthesis
- Text Readability and Simplification
- Signal Processing top 10%
- Music and Audio Processing
Papers in
-
- Natural Language Processing Techniques 12
- Topic Modeling 10
- Speech and dialogue systems 5
- Speech Recognition and Synthesis 4
- Authorship Attribution and Profiling 2
- Advanced Text Analysis Techniques 1
-
- Music and Audio Processing 4
- Speech and Audio Processing 2
- Co-authors
- Benoît Favre (3 shared papers)Dan Klein (2 shared papers)Taylor Berg-Kirkpatrick (1 shared paper)Amarnag Subramanya (1 shared paper)Oriol Vinyals (1 shared paper)Cliff Brunk (1 shared paper)Dilek Hakkani‐Tür (4 shared papers)Yang Liu (1 shared paper)
- Journals
- National Conference on Artificial Intelligence (1 paper)Meeting of the Association for Computational Linguistics (1 paper)
- Partner nations
- United StatesGermany
In The Last Decade
Dan Gillick
16 papers receiving 639 citations
Peers
Comparison fields: 5 of 46
- Artificial Intelligence 666
- Signal Processing 58
- Computer Vision and Pattern Recognition 66
- Information Systems 61
- Computer Science Applications 14
Countries citing papers authored by Dan Gillick
This map shows the geographic impact of Dan Gillick'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 Dan Gillick with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Dan Gillick more than expected).
Fields of papers citing papers by Dan Gillick
This network shows the impact of papers produced by Dan Gillick. 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 Dan Gillick. The network helps show where Dan Gillick may publish in the future.
Co-authors
The 23 scholars most cited alongside Dan Gillick, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2009 | 169 | |
| 2 | Jointly Learning to Extract and Compress | 2011 | 122 |
| 3 | 2016 | 112 | |
| 4 | 2006 | 59 | |
| 5 | 2009 | 57 | |
| 6 | 2009 | 56 | |
| 7 | Non-Expert Evaluation of Summarization Systems is Risky | 2010 | 43 |
| 8 | Who’s Calling? Demographics of Mobile Phone Use in Rwanda | 2010 | 25 |
| 9 | 2008 | 22 | |
| 10 | 2011 | 17 | |
| 11 | 2012 | 13 | |
| 12 | 2010 | 12 | |
| 13 | 2006 | 7 | |
| 14 | 2006 | 3 | |
| 15 | 2008 | 2 | |
| 16 | 2005 | 1 |
About Dan Gillick
Dan Gillick is a scholar working on Artificial Intelligence, Signal Processing, Sociology and Political Science, Information Systems and Computer Vision and Pattern Recognition, having authored 16 papers that have together received 720 indexed citations. Recurring topics across this work include Natural Language Processing Techniques (12 papers), Topic Modeling (10 papers), Speech and dialogue systems (5 papers), Speech Recognition and Synthesis (4 papers), Music and Audio Processing (4 papers), Speech and Audio Processing (2 papers), Authorship Attribution and Profiling (2 papers) and Advanced Text Analysis Techniques (1 paper). The work is most often cited by research in Artificial Intelligence (666 citations), Signal Processing (58 citations), Computer Vision and Pattern Recognition (66 citations), Information Systems (61 citations) and Computer Science Applications (14 citations). Dan Gillick has collaborated with scholars based in United States and Germany. Frequent co-authors include Benoît Favre, Dan Klein, Taylor Berg-Kirkpatrick, Amarnag Subramanya, Oriol Vinyals, Cliff Brunk, Dilek Hakkani‐Tür, Yang Liu, Korbinian Riedhammer and James Zhang. Their work appears in journals such as National Conference on Artificial Intelligence and Meeting of the Association for Computational Linguistics.
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.