David Andrzejewski
Impact in
- General Social Sciences top 0.5%
- Computational and Text Analysis Methods
- Artificial Intelligence top 2%
- Topic Modeling
- Sentiment Analysis and Opinion Mining
- Advanced Text Analysis Techniques
- Text and Document Classification Technologies
Papers in
-
- Topic Modeling 5
- Sentiment Analysis and Opinion Mining 1
- Bayesian Methods and Mixture Models 1
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- Information Retrieval and Search Behavior 3
- Co-authors
- Xiaojin Zhu (8 shared papers)Mark W. Craven (3 shared papers)David J. Buttler (2 shared papers)Philip Kegelmeyer (1 shared paper)Keith Stevens (1 shared paper)Andrew B. Goldberg (3 shared papers)Jurgen Van Gael (2 shared papers)Benjamin Recht (1 shared paper)
- Journals
- Lecture notes in computer science (1 paper)International Conference on Machine Learning (1 paper)North American Chapter of the Association for Computational Linguistics (1 paper)Empirical Methods in Natural Language Processing (1 paper)Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE (1 paper)
- Partner nations
- United StatesCanada
In The Last Decade
David Andrzejewski
11 papers receiving 1.1k citations
David Andrzejewski's Hit Papers
Peers
Comparison fields: 5 of 89
- General Social Sciences 146
- Artificial Intelligence 747
- Information Systems 222
- Software 25
- Computer Vision and Pattern Recognition 104
Countries citing papers authored by David Andrzejewski
This map shows the geographic impact of David Andrzejewski'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 David Andrzejewski with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites David Andrzejewski more than expected).
Fields of papers citing papers by David Andrzejewski
This network shows the impact of papers produced by David Andrzejewski. 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 David Andrzejewski. The network helps show where David Andrzejewski may publish in the future.
Co-authors
The 12 scholars most cited alongside David Andrzejewski, 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 | 321 | |
| 2 | Exploring Topic Coherence over Many Models and Many Topics Hit paper breakdown → | 2012 | 316 |
| 3 | Improving Diversity in Ranking using Absorbing Random Walks | 2007 | 167 |
| 4 | 2009 | 109 | |
| 5 | 2011 | 105 | |
| 6 | 2007 | 65 | |
| 7 | 2009 | 57 | |
| 8 | 2011 | 48 | |
| 9 | Ranking Biomedical Passages for Relevance and Diversity: University of Wisconsin, Madison at TREC Genomics 2006. | 2006 | 16 |
| 10 | 2010 | 6 | |
| 11 | Modeling Protein-Protein Interactions in Biomedical Abstracts with Latent Dirichlet Allocation | 2006 | 1 |
About David Andrzejewski
David Andrzejewski is a scholar working on Artificial Intelligence, Information Systems, Software, Visual Arts and Performing Arts and Archeology, having authored 11 papers that have together received 1.2k indexed citations. Recurring topics across this work include Topic Modeling (5 papers), Information Retrieval and Search Behavior (3 papers), Image Processing and 3D Reconstruction (1 paper), Cultural Heritage Materials Analysis (1 paper), Biomedical Text Mining and Ontologies (1 paper), Software Testing and Debugging Techniques (1 paper), Sentiment Analysis and Opinion Mining (1 paper) and Bayesian Methods and Mixture Models (1 paper). The work is most often cited by research in General Social Sciences (146 citations), Artificial Intelligence (747 citations), Information Systems (222 citations), Software (25 citations) and Computer Vision and Pattern Recognition (104 citations). David Andrzejewski has collaborated with scholars based in United States and Canada. Frequent co-authors include Xiaojin Zhu, Mark W. Craven, David J. Buttler, Philip Kegelmeyer, Keith Stevens, Andrew B. Goldberg, Jurgen Van Gael, Benjamin Recht, Ben Liblit and Nathanael R. Fillmore. Their work appears in journals such as Lecture notes in computer science, International Conference on Machine Learning, North American Chapter of the Association for Computational Linguistics, Empirical Methods in Natural Language Processing and Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE.
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.