Joshua Goodman
- Artificial Intelligence top 0.2%
- Information Systems top 1%
- Computer Vision and Pattern Recognition top 2%
- Signal Processing top 2%
- Computer Networks and Communications top 5%
- Co-authors
- Stanley F. ChenWen-tau YihVitor R. CarvalhoJianfeng GaoDavid HeckermanGordon V. CormackKeith SteuryGina Venolia
- Topics
- Topic Modeling (16 papers)Natural Language Processing Techniques (16 papers)Spam and Phishing Detection (9 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
- Information Systems 722
- Computer Vision and Pattern Recognition 393
- Signal Processing 344
- Computer Networks and Communications 251
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 of co-authors of Joshua Goodman
This figure shows the co-authorship network connecting the top 25 collaborators of Joshua Goodman. A scholar is included among the top collaborators of Joshua Goodman based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Joshua Goodman. Joshua Goodman is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | The Impact of Item Position Change on Item Parameters and Common Equating Results under the 3PL Model | 5 |
| 2 | 2 | |
| 3 | Multi-document summarization by maximizing informative content-words | 91 |
| 4 | Learning at Low False Positive Rates. | 27 |
| 5 | Online Discriminative Spam Filter Training. | 50 |
| 6 | 15 | |
| 7 | 3 | |
| 8 | 53 | |
| 9 | IP Addresses in Email Clients. | 18 |
| 10 | 1 | |
| 11 | The state of the art in language modeling | 1 |
| 12 | 22 | |
| 13 | 75 | |
| 14 | 27 | |
| 15 | 35 | |
| 16 | 37 | |
| 17 | Semiring parsing | 94 |
| 18 | 36 | |
| 19 | 104 | |
| 20 | 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) and Spam and Phishing Detection (9 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.