Ron Bekkerman
- Artificial Intelligence top 1%
- Text and Document Classification Technologies 5
- Advanced Text Analysis Techniques 4
- Topic Modeling 3
- Information Systems top 1%
- Spam and Phishing Detection 5
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- Complex Network Analysis Techniques 7
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- Image Retrieval and Classification Techniques 3
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- Housing Market and Economics 5
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- Data Management and Algorithms 2
- Co-authors
- Andrew McCallumMikhail BilenkoJohn LangfordRan El‐YanivNaftali TishbyYoad WinterAron CulottaGary B. Huang
- Partner nations
- United StatesIsraelCanada
In The Last Decade
Ron Bekkerman
32 papers receiving 1.2k citations
Peers
Comparison fields: 5 of 106
- Artificial Intelligence 862
- Information Systems 467
- Statistical and Nonlinear Physics 194
- Management Science and Operations Research 183
- Computer Vision and Pattern Recognition 216
Countries citing papers authored by Ron Bekkerman
This map shows the geographic impact of Ron Bekkerman'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 Ron Bekkerman with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ron Bekkerman more than expected).
Fields of papers citing papers by Ron Bekkerman
This network shows the impact of papers produced by Ron Bekkerman. 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 Ron Bekkerman. The network helps show where Ron Bekkerman may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Ron Bekkerman, 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 | 2024 | 0 | |
| 2 | 2022 | 16 | |
| 3 | 2021 | 8 | |
| 4 | 2021 | 4 | |
| 5 | 2020 | 7 | |
| 6 | 2019 | 2 | |
| 7 | 2018 | 22 | |
| 8 | 2017 | 5 | |
| 9 | 2017 | 1 | |
| 10 | Automatic Discovery of Prior Art: Big Data to the Rescue of the Patent System | 2016 | 3 |
| 11 | 2014 | 1 | |
| 12 | 2012 | 16 | |
| 13 | 2011 | 31 | |
| 14 | 2011 | 136 | |
| 15 | Scaling up Machine Learning | 2011 | 14 |
| 16 | Combinatorial markov random fields and their applications to information organization | 2008 | 2 |
| 17 | Interactive clustering of text collections according to a user-specified criterion | 2007 | 24 |
| 18 | Automatic Categorization of Email into Folders: Benchmark Experiments on Enron and SRI Corpora | 2005 | 91 |
| 19 | Extracting Social Networks and Contact Information From Email and the Web | 2004 | 151 |
| 20 | Distributional word clusters vs. words for text categorization | 2003 | 186 |
About Ron Bekkerman
Ron Bekkerman is a scholar working on Statistical and Nonlinear Physics, Artificial Intelligence, Information Systems, Marketing and General Social Sciences, having authored 35 papers that have together received 1.3k indexed citations. Recurring topics across this work include Complex Network Analysis Techniques (7 papers), Spam and Phishing Detection (5 papers), Housing Market and Economics (5 papers), Text and Document Classification Technologies (5 papers), Advanced Text Analysis Techniques (4 papers), Topic Modeling (3 papers), Image Retrieval and Classification Techniques (3 papers) and Data Management and Algorithms (2 papers). The work is most often cited by research in Artificial Intelligence (862 citations), Information Systems (467 citations), Statistical and Nonlinear Physics (194 citations), Management Science and Operations Research (183 citations) and Computer Vision and Pattern Recognition (216 citations). Ron Bekkerman has collaborated with scholars based in United States, Israel and Canada. Frequent co-authors include Andrew McCallum, Mikhail Bilenko, John Langford, Ran El‐Yaniv, Naftali Tishby, Yoad Winter, Aron Culotta, Andrew McCallum, Gary B. Huang and Jiwoon Jeon. Their work appears in journals such as Big Data, PLoS ONE, Information Sciences, Marketing Science and Manufacturing & Service Operations Management.
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.