Jack G. Conrad
- Artificial Intelligence top 5%
- Information Systems top 5%
- Political Science and International Relations top 10%
- Management Science and Operations Research top 10%
- Computer Networks and Communications
- Co-authors
- Frank SchilderKhalid Al-KofahiQiang LüJochen L. LeidnerYing ZhaoGeorge KarypisJohn ZeleznikowL. Karl Branting
- Topics
- Topic Modeling (13 papers)Artificial Intelligence in Law (11 papers)Web Data Mining and Analysis (9 papers)
- Journals
- ACM Transactions on Information SystemsArtificial Intelligence and LawTheory and applications of categories
- Partner nations
- United StatesAustraliaIndia
In The Last Decade
Jack G. Conrad
29 papers receiving 291 citations
Peers
Comparison fields: 5 of 48
- Artificial Intelligence 244
- Information Systems 121
- Political Science and International Relations 90
- Management Science and Operations Research 39
- Computer Networks and Communications 27
Countries citing papers authored by Jack G. Conrad
This map shows the geographic impact of Jack G. Conrad'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 Jack G. Conrad with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jack G. Conrad more than expected).
Fields of papers citing papers by Jack G. Conrad
This network shows the impact of papers produced by Jack G. Conrad. 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 Jack G. Conrad. The network helps show where Jack G. Conrad may publish in the future.
Co-authorship network of co-authors of Jack G. Conrad
This figure shows the co-authorship network connecting the top 25 collaborators of Jack G. Conrad. A scholar is included among the top collaborators of Jack G. Conrad 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 Jack G. Conrad. Jack G. Conrad is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 2 | |
| 2 | 10 | |
| 3 | 2 | |
| 4 | 4 | |
| 5 | Semi-Supervised Events Clustering in News Retrieval. | 8 |
| 6 | 10 | |
| 7 | 5 | |
| 8 | 5 | |
| 9 | 13 | |
| 10 | Thomson Reuters at TAC 2008: Aggressive Filtering with FastSum for Update and Opinion Summarization. | 9 |
| 11 | 2 | |
| 12 | 14 | |
| 13 | E-Discovery Revisited: A Broader Perspective for IR Researchers | 10 |
| 14 | 58 | |
| 15 | 2 | |
| 16 | 1 | |
| 17 | 45 | |
| 18 | 4 | |
| 19 | 7 | |
| 20 | 5 |
About Jack G. Conrad
Jack G. Conrad is a scholar working on Information Systems, Artificial Intelligence and Law, having authored 29 papers that have together received 342 indexed citations. Recurring topics across this work include Topic Modeling (13 papers), Artificial Intelligence in Law (11 papers) and Web Data Mining and Analysis (9 papers). The work is most often cited by research in Artificial Intelligence (244 citations), Information Systems (121 citations) and Political Science and International Relations (90 citations). Jack G. Conrad has collaborated with scholars based in United States, Australia and India. Frequent co-authors include Frank Schilder, Khalid Al-Kofahi, Qiang Lü, Jochen L. Leidner, Ying Zhao, George Karypis, John Zeleznikow, L. Karl Branting, Andrew Vold and Michael A. Bender. Their work appears in journals such as ACM Transactions on Information Systems, Artificial Intelligence and Law and Theory and applications of categories.
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.