Robert Ragno
Impact in
- Information Systems top 1%
- Recommender Systems and Techniques
- Information Retrieval and Search Behavior
- Web Data Mining and Analysis
- Expert finding and Q&A systems
- Marketing top 5%
- Consumer Market Behavior and Pricing
Papers in ⓘ
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- AI-based Problem Solving and Planning 2
- Neural Networks and Applications 1
- Text and Document Classification Technologies 1
- Advanced Software Engineering Methodologies 1
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- Web Data Mining and Analysis 2
- Information Retrieval and Search Behavior 2
- Co-authors
- Matthew Richardson (1 shared paper)Ewa Dominowska (1 shared paper)Eugene Agichtein (1 shared paper)Susan Dumais (1 shared paper)Eric Brill (1 shared paper)Brian C. Williams (1 shared paper)Chris Burges (2 shared papers)Quoc V. Le (1 shared paper)
- Journals
- Discrete Applied Mathematics (1 paper)Current HIV Research (1 paper)The MIT Press eBooks (1 paper)DSpace@MIT (Massachusetts Institute of Technology) (1 paper)
- Partner nations
- United StatesUnited Kingdom
In The Last Decade
Robert Ragno
8 papers receiving 1.1k citations
Hit Papers
Peers
Comparison fields: 5 of 82
- Information Systems 730
- Marketing 190
- Artificial Intelligence 476
- Software 56
- Management Science and Operations Research 172
Countries citing papers authored by Robert Ragno
This map shows the geographic impact of Robert Ragno'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 Robert Ragno with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Robert Ragno more than expected).
Fields of papers citing papers by Robert Ragno
This network shows the impact of papers produced by Robert Ragno. 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 Robert Ragno. The network helps show where Robert Ragno may publish in the future.
Co-authors
The 13 scholars most cited alongside Robert Ragno, 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 | Predicting clicks Hit paper breakdown → | 2007 | 652 |
| 2 | Learning user interaction models for predicting web search result preferences Hit paper breakdown → | 2006 | 322 |
| 3 | 2007 | 93 | |
| 4 | 2007 | 77 | |
| 5 | 2005 | 51 | |
| 6 | 2001 | 21 | |
| 7 | 2007 | 6 | |
| 8 | Solving optimal satisfiability problems through clause-directed A | 2002 | 2 |
About Robert Ragno
Robert Ragno is a scholar working on Artificial Intelligence, Information Systems, Computer Vision and Pattern Recognition, Signal Processing and Software, having authored 8 papers that have together received 1.2k indexed citations. Recurring topics across this work include AI-based Problem Solving and Planning (2 papers), Web Data Mining and Analysis (2 papers), Model-Driven Software Engineering Techniques (2 papers), Information Retrieval and Search Behavior (2 papers), Data Management and Algorithms (1 paper), Neural Networks and Applications (1 paper), Text and Document Classification Technologies (1 paper) and Advanced Software Engineering Methodologies (1 paper). The work is most often cited by research in Information Systems (730 citations), Marketing (190 citations), Artificial Intelligence (476 citations), Software (56 citations) and Management Science and Operations Research (172 citations). Robert Ragno has collaborated with scholars based in United States and United Kingdom. Frequent co-authors include Matthew Richardson, Ewa Dominowska, Eugene Agichtein, Susan Dumais, Eric Brill, Brian C. Williams, Chris Burges, Quoc V. Le, Cormac Herley and Michel D. Ingham. Their work appears in journals such as Discrete Applied Mathematics, Current HIV Research, The MIT Press eBooks and DSpace@MIT (Massachusetts Institute of Technology).
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.