Joshua Goodman
- Artificial Intelligence top 0.2%
- Topic Modeling 16
- Natural Language Processing Techniques 16
- Speech Recognition and Synthesis 8
- Speech and dialogue systems 4
- Internet Traffic Analysis and Secure E-voting 4
- Human-Computer Interaction top 2%
- Information Systems top 1%
- Spam and Phishing Detection 9
- Signal Processing top 2%
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- Psychometric Methodologies and Testing 5
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- Advanced Statistical Modeling Techniques 4
- Co-authors
- Stanley F. ChenWen-tau YihVitor R. CarvalhoJianfeng GaoDavid HeckermanGordon V. CormackKeith SteuryGina Venolia
- Journals
- Communications of the ACM (1 paper)Scientific American (1 paper)Educational and Psychological Measurement (2 papers)
- Partner nations
- United StatesUnited KingdomChina
In The Last Decade
Joshua Goodman
42 papers receiving 3.2k citations
Hit Papers
Peers
Comparison fields: 5 of 118
- Artificial Intelligence 2.9k
- Human-Computer Interaction 189
- Information Systems 722
- Signal Processing 344
- Computer Vision and Pattern Recognition 393
Countries citing papers authored by Joshua Goodman
This map shows the geographic impact of Joshua Goodman'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 Joshua Goodman with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Joshua Goodman more than expected).
Fields of papers citing papers by Joshua Goodman
This network shows the impact of papers produced by Joshua Goodman. 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 Joshua Goodman. The network helps show where Joshua Goodman may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Joshua Goodman, 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 | The Impact of Item Position Change on Item Parameters and Common Equating Results under the 3PL Model | 2012 | 5 |
| 2 | 2008 | 2 | |
| 3 | Multi-document summarization by maximizing informative content-words | 2007 | 91 |
| 4 | Learning at Low False Positive Rates. | 2006 | 27 |
| 5 | Online Discriminative Spam Filter Training. | 2006 | 50 |
| 6 | 2005 | 15 | |
| 7 | 2005 | 3 | |
| 8 | 2005 | 53 | |
| 9 | IP Addresses in Email Clients. | 2004 | 18 |
| 10 | 2004 | 1 | |
| 11 | The state of the art in language modeling | 2002 | 1 |
| 12 | 2002 | 22 | |
| 13 | 2001 | 75 | |
| 14 | 2001 | 27 | |
| 15 | 2000 | 35 | |
| 16 | 2000 | 37 | |
| 17 | Semiring parsing | 1999 | 94 |
| 18 | 1997 | 36 | |
| 19 | 1996 | 104 | |
| 20 | 1996 | 490 |
About Joshua Goodman
Joshua Goodman is a scholar working on Artificial Intelligence, Information Systems and Management Science and Operations Research, having authored 45 papers that have together received 3.7k indexed citations. Recurring topics across this work include Topic Modeling (16 papers), Natural Language Processing Techniques (16 papers), Spam and Phishing Detection (9 papers), Speech Recognition and Synthesis (8 papers), Psychometric Methodologies and Testing (5 papers), Speech and dialogue systems (4 papers), Advanced Statistical Modeling Techniques (4 papers) and Internet Traffic Analysis and Secure E-voting (4 papers). The work is most often cited by research in Artificial Intelligence (2.9k citations), Human-Computer Interaction (189 citations) and Information Systems (722 citations). Joshua Goodman has collaborated with scholars based in United States, United Kingdom and China. Frequent co-authors include Stanley F. Chen, Wen-tau Yih, Vitor R. Carvalho, Jianfeng Gao, David Heckerman, Gordon V. Cormack, Keith Steury, Gina Venolia, Chauncey R. Parker and Mingjing Li. Their work appears in journals such as Communications of the ACM, Scientific American and Educational and Psychological Measurement.
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.