Marko Balabanović
Impact in
- Information Systems top 0.2%
- Recommender Systems and Techniques
- Web Data Mining and Analysis
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- Image Retrieval and Classification Techniques
- Video Analysis and Summarization
Papers in
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- Recommender Systems and Techniques 5
- Web Data Mining and Analysis 2
- Information Retrieval and Search Behavior 1
- Co-authors
- Yoav ShohamGregory J. WolffKarl PflegerPhilippe LalandaBarbara Hayes‐RothIllah NourbakhshReid SimmonsErann Gat
- Journals
- User Modeling and User-Adapted Interaction (1 paper)IEEE Transactions on Software Engineering (1 paper)Digital Health (1 paper)AI Magazine (1 paper)Communications of the ACM (1 paper)
- Partner nations
- United StatesJapan
In The Last Decade
Marko Balabanović
10 papers receiving 2.3k citations
Hit Papers
Peers
Comparison fields: 5 of 84
- Information Systems 2.0k
- Computer Vision and Pattern Recognition 809
- Signal Processing 304
- Artificial Intelligence 891
- Computer Science Applications 133
Countries citing papers authored by Marko Balabanović
This map shows the geographic impact of Marko Balabanović'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 Marko Balabanović with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Marko Balabanović more than expected).
Fields of papers citing papers by Marko Balabanović
This network shows the impact of papers produced by Marko Balabanović. 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 Marko Balabanović. The network helps show where Marko Balabanović may publish in the future.
Co-authorship network
The 12 scholars most cited alongside Marko Balabanović, 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 | 2022 | 4 | |
| 2 | 2000 | 153 | |
| 3 | Learning to surf: multiagent systems for adaptive web page recommendation | 1998 | 22 |
| 4 | 1998 | 47 | |
| 5 | Content-based, collaborative recommendation | 1997 | 247 |
| 6 | 1997 | 130 | |
| 7 | Fab Hit paper breakdown → | 1997 | 1833 |
| 8 | An Adaptive Agent for Automated Web Browsing | 1997 | 50 |
| 9 | 1995 | 74 | |
| 10 | 1993 | 22 |
About Marko Balabanović
Marko Balabanović is a scholar working on Information Systems, Human-Computer Interaction, Computer Vision and Pattern Recognition, Speech and Hearing and Artificial Intelligence, having authored 10 papers that have together received 2.6k indexed citations. Recurring topics across this work include Recommender Systems and Techniques (5 papers), Modular Robots and Swarm Intelligence (2 papers), Web Data Mining and Analysis (2 papers), Information Retrieval and Search Behavior (1 paper), Respiratory viral infections research (1 paper), Optimization and Search Problems (1 paper), Multi-Agent Systems and Negotiation (1 paper) and Advanced Software Engineering Methodologies (1 paper). The work is most often cited by research in Information Systems (2.0k citations), Computer Vision and Pattern Recognition (809 citations), Signal Processing (304 citations), Artificial Intelligence (891 citations) and Computer Science Applications (133 citations). Marko Balabanović has collaborated with scholars based in United States and Japan. Frequent co-authors include Yoav Shoham, Gregory J. Wolff, Karl Pfleger, Philippe Lalanda, Barbara Hayes‐Roth, Illah Nourbakhsh, Reid Simmons, Erann Gat, David Van Vactor and David Plans. Their work appears in journals such as User Modeling and User-Adapted Interaction, IEEE Transactions on Software Engineering, Digital Health, AI Magazine and Communications of the ACM.
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.