Konstantin Bauman
- Information Systems top 5%
- Artificial Intelligence top 10%
- Sociology and Political Science
- Computer Vision and Pattern Recognition
- Management Science and Operations Research
- Co-authors
- Alexander TuzhilinBing LiuMoshe UngerGediminas AdomavičiusBamshad MobasherFrancesco Ricci⋆
- Topics
- Recommender Systems and Techniques (14 papers)Advanced Graph Neural Networks (5 papers)Data Management and Algorithms (5 papers)
- Journals
- MIS QuarterlyInformation Systems ResearchACM Transactions on Management Information Systems
- Partner nations
- United StatesIsraelItaly
In The Last Decade
Konstantin Bauman
17 papers receiving 227 citations
Peers
Comparison fields: 5 of 43
- Information Systems 153
- Artificial Intelligence 150
- Sociology and Political Science 40
- Computer Vision and Pattern Recognition 21
- Management Science and Operations Research 19
Countries citing papers authored by Konstantin Bauman
This map shows the geographic impact of Konstantin Bauman'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 Konstantin Bauman with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Konstantin Bauman more than expected).
Fields of papers citing papers by Konstantin Bauman
This network shows the impact of papers produced by Konstantin Bauman. 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 Konstantin Bauman. The network helps show where Konstantin Bauman may publish in the future.
Co-authorship network of co-authors of Konstantin Bauman
This figure shows the co-authorship network connecting the top 25 collaborators of Konstantin Bauman. A scholar is included among the top collaborators of Konstantin Bauman 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 Konstantin Bauman. Konstantin Bauman is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 1 | |
| 3 | 2 | |
| 4 | 2 | |
| 5 | 2 | |
| 6 | 16 | |
| 7 | 3 | |
| 8 | 1 | |
| 9 | 1 | |
| 10 | 2 | |
| 11 | 24 | |
| 12 | 19 | |
| 13 | 121 | |
| 14 | Recommending items with conditions enhancing user experiences based on sentiment analysis of reviews | 6 |
| 15 | Virtual Power Outage Detection Using Social Sensors | 3 |
| 16 | Discovering Contextual Information from User Reviews for Recommendation Purposes. | 22 |
| 17 | Recommending Learning Materials to Students by Identifying their Knowledge Gaps. | 2 |
| 18 | 2 |
About Konstantin Bauman
Konstantin Bauman is a scholar working on Information Systems, Signal Processing and Communication, having authored 18 papers that have together received 229 indexed citations. Recurring topics across this work include Recommender Systems and Techniques (14 papers), Advanced Graph Neural Networks (5 papers) and Data Management and Algorithms (5 papers). The work is most often cited by research in Information Systems (153 citations), Computational Mathematics (3 citations) and Artificial Intelligence (150 citations). Konstantin Bauman has collaborated with scholars based in United States, Israel and Italy. Frequent co-authors include Alexander Tuzhilin, Bing Liu, Moshe Unger, Gediminas Adomavičius, Bamshad Mobasher, Bing Liu and Francesco Ricci⋆. Their work appears in journals such as MIS Quarterly, Information Systems Research and ACM Transactions on Management Information Systems.
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.