Richard D. Lawrence
Impact in
- Artificial Intelligence top 2%
- Sentiment Analysis and Opinion Mining
- Advanced Text Analysis Techniques
- Text and Document Classification Technologies
- Topic Modeling
Papers in
-
- Text and Document Classification Technologies 8
- Machine Learning and Algorithms 5
- Machine Learning and Data Classification 4
- Domain Adaptation and Few-Shot Learning 3
- Algorithms and Data Compression 3
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- Image Retrieval and Classification Techniques 4
- Advanced Image and Video Retrieval Techniques 3
- Co-authors
- Prem Melville (10 shared papers)Wojciech Gryc (2 shared papers)George Almási (4 shared papers)Jingrui He (6 shared papers)Vladimir Kotlyar (1 shared paper)Marisa Viveros (1 shared paper)Sastry Duri (1 shared paper)Holly Rushmeier (3 shared papers)
- Journals
- IBM Systems Journal (4 papers)Data Mining and Knowledge Discovery (3 papers)SAE technical papers on CD-ROM/SAE technical paper series (2 papers)IBM Journal of Research and Development (2 papers)Parallel Computing (1 paper)
- Partner nations
- United StatesIsraelUnited Kingdom
In The Last Decade
Richard D. Lawrence
45 papers receiving 1.3k citations
Peers
Comparison fields: 5 of 136
- Artificial Intelligence 678
- Computer Science Applications 101
- Hardware and Architecture 101
- Information Systems 333
- Marketing 111
Countries citing papers authored by Richard D. Lawrence
This map shows the geographic impact of Richard D. Lawrence'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 Richard D. Lawrence with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Richard D. Lawrence more than expected).
Fields of papers citing papers by Richard D. Lawrence
This network shows the impact of papers produced by Richard D. Lawrence. 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 Richard D. Lawrence. The network helps show where Richard D. Lawrence may publish in the future.
Co-authors
The 25 scholars most cited alongside Richard D. Lawrence, 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 45 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2009 | 325 | |
| 2 | 2001 | 146 | |
| 3 | 2004 | 111 | |
| 4 | 2000 | 75 | |
| 5 | 2002 | 68 | |
| 6 | 1999 | 67 | |
| 7 | 2011 | 60 | |
| 8 | 2006 | 52 | |
| 9 | 1994 | 46 | |
| 10 | Amygdalin toxicity studies in rats predict chronic cyanide poisoning in humans. | 1981 | 42 |
| 11 | 2009 | 40 | |
| 12 | 2008 | 34 | |
| 13 | 2012 | 31 | |
| 14 | Multiple Instance Learning on Structured Data | 2011 | 30 |
| 15 | 2013 | 27 | |
| 16 | 2003 | 26 | |
| 17 | 2007 | 19 | |
| 18 | 2009 | 17 | |
| 19 | 2009 | 15 | |
| 20 | 2011 | 15 |
About Richard D. Lawrence
Richard D. Lawrence is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Information Systems, Computer Networks and Communications and Marketing, having authored 45 papers that have together received 1.4k indexed citations. Recurring topics across this work include Text and Document Classification Technologies (8 papers), Machine Learning and Algorithms (5 papers), Machine Learning and Data Classification (4 papers), Image Retrieval and Classification Techniques (4 papers), Domain Adaptation and Few-Shot Learning (3 papers), Supply Chain and Inventory Management (3 papers), Advanced Image and Video Retrieval Techniques (3 papers) and Algorithms and Data Compression (3 papers). The work is most often cited by research in Artificial Intelligence (678 citations), Computer Science Applications (101 citations), Hardware and Architecture (101 citations), Information Systems (333 citations) and Marketing (111 citations). Richard D. Lawrence has collaborated with scholars based in United States, Israel and United Kingdom. Frequent co-authors include Prem Melville, Wojciech Gryc, George Almási, Jingrui He, Vladimir Kotlyar, Marisa Viveros, Sastry Duri, Holly Rushmeier, Yan Liu and Dan Zhang. Their work appears in journals such as IBM Systems Journal, Data Mining and Knowledge Discovery, SAE technical papers on CD-ROM/SAE technical paper series, IBM Journal of Research and Development and Parallel Computing.
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.