Dan Pelleg
Impact in
- Signal Processing top 1%
- Data Management and Algorithms
- Artificial Intelligence top 1%
- Advanced Clustering Algorithms Research
- Topic Modeling
- Anomaly Detection Techniques and Applications
Papers in
-
- Expert finding and Q&A systems 8
- Data Mining Algorithms and Applications 7
- Web Data Mining and Analysis 5
- Cloud Computing and Resource Management 4
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- Topic Modeling 8
- Co-authors
- Andrew Moore (8 shared papers)Yoelle Maarek (7 shared papers)Elad Yom‐Tov (6 shared papers)Idan Szpektor (5 shared papers)Sigalit Ur (2 shared papers)Michal Jacovi (2 shared papers)David Carmel (3 shared papers)Adam Darlow (2 shared papers)
- Journals
- PLoS ONE (2 papers)The VLDB Journal (1 paper)Journal of Computational Biology (1 paper)IBM Journal of Research and Development (1 paper)ACM Transactions on Information Systems (1 paper)
- Partner nations
- United StatesIsraelUnited Kingdom
In The Last Decade
Dan Pelleg
40 papers receiving 3.0k citations
Dan Pelleg's Hit Papers
Peers
Comparison fields: 5 of 151
- Signal Processing 669
- Artificial Intelligence 1.7k
- Information Systems 1.1k
- Computer Vision and Pattern Recognition 696
- Computer Science Applications 143
Countries citing papers authored by Dan Pelleg
This map shows the geographic impact of Dan Pelleg'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 Pelleg with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Dan Pelleg more than expected).
Fields of papers citing papers by Dan Pelleg
This network shows the impact of papers produced by Dan Pelleg. 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 Pelleg. The network helps show where Dan Pelleg may publish in the future.
Co-authors
The 25 scholars most cited alongside Dan Pelleg, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 42 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | X-means: Extending K-means with Efficient Estimation of the Number of Clusters Hit paper breakdown → | 2000 | 1712 |
| 2 | 1999 | 296 | |
| 3 | 1998 | 236 | |
| 4 | 2006 | 161 | |
| 5 | Active Learning for Anomaly and Rare-Category Detection | 2004 | 111 |
| 6 | 2012 | 91 | |
| 7 | 2007 | 68 | |
| 8 | 2012 | 62 | |
| 9 | 2011 | 53 | |
| 10 | Ephemeral Document Clustering for Web Applications | 2001 | 53 |
| 11 | 2013 | 48 | |
| 12 | 1999 | 44 | |
| 13 | 1998 | 37 | |
| 14 | Overview of the TREC 2015 LiveQA Track. | 2015 | 26 |
| 15 | 2012 | 26 | |
| 16 | Mixtures of Rectangles: Interpretable Soft Clustering | 2001 | 25 |
| 17 | 2008 | 24 | |
| 18 | 2009 | 20 | |
| 19 | 2017 | 16 | |
| 20 | 2013 | 15 |
About Dan Pelleg
Dan Pelleg is a scholar working on Information Systems, Artificial Intelligence, Computer Science Applications, Computer Networks and Communications and Signal Processing, having authored 42 papers that have together received 3.2k indexed citations. Recurring topics across this work include Expert finding and Q&A systems (8 papers), Topic Modeling (8 papers), Data Mining Algorithms and Applications (7 papers), Mobile Crowdsensing and Crowdsourcing (6 papers), Web Data Mining and Analysis (5 papers), Cloud Computing and Resource Management (4 papers), Data Management and Algorithms (4 papers) and Software System Performance and Reliability (4 papers). The work is most often cited by research in Signal Processing (669 citations), Artificial Intelligence (1.7k citations), Information Systems (1.1k citations), Computer Vision and Pattern Recognition (696 citations) and Computer Science Applications (143 citations). Dan Pelleg has collaborated with scholars based in United States, Israel and United Kingdom. Frequent co-authors include Andrew Moore, Yoelle Maarek, Elad Yom‐Tov, Idan Szpektor, Sigalit Ur, Michal Jacovi, David Carmel, Adam Darlow, Gideon Dror and Oleg Rokhlenko. Their work appears in journals such as PLoS ONE, The VLDB Journal, Journal of Computational Biology, IBM Journal of Research and Development and ACM Transactions on Information Systems.
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.