Marko Krema
Impact in
- Artificial Intelligence top 10%
- Advanced Text Analysis Techniques
- Sentiment Analysis and Opinion Mining
- Topic Modeling
- Text and Document Classification Technologies
- Natural Language Processing Techniques
- Information Systems top 10%
- Web Data Mining and Analysis
Papers in
-
- Web Data Mining and Analysis 2
- Data Mining Algorithms and Applications 1
-
- Advanced Text Analysis Techniques 3
- Sentiment Analysis and Opinion Mining 2
- Topic Modeling 1
- Co-authors
- Andrew Fano (4 shared papers)Rayid Ghani (4 shared papers)Katharina Probst (2 shared papers)Yan Liu (2 shared papers)Chad Cumby (2 shared papers)Sohini Roychowdhury (1 shared paper)Brian C. J. Moore (1 shared paper)Arijit Mukherjee (2 shared papers)
- Journals
- ACM SIGKDD Explorations Newsletter (1 paper)
- Partner nations
- United StatesSwitzerland
In The Last Decade
Marko Krema
6 papers receiving 194 citations
Peers
Comparison fields: 5 of 39
- Artificial Intelligence 152
- Information Systems 99
- Marketing 36
- Management Science and Operations Research 23
- Computer Science Applications 6
Countries citing papers authored by Marko Krema
This map shows the geographic impact of Marko Krema'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 Krema with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Marko Krema more than expected).
Fields of papers citing papers by Marko Krema
This network shows the impact of papers produced by Marko Krema. 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 Krema. The network helps show where Marko Krema may publish in the future.
Co-authors
The 10 scholars most cited alongside Marko Krema, 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 | 2006 | 138 | |
| 2 | Semi-supervised learning of attribute-value pairs from product descriptions | 2007 | 35 |
| 3 | 2004 | 23 | |
| 4 | 2005 | 15 | |
| 5 | 2023 | 7 | |
| 6 | 2024 | 2 |
About Marko Krema
Marko Krema is a scholar working on Information Systems, Artificial Intelligence, Marketing, Management Science and Operations Research and Infectious Diseases, having authored 6 papers that have together received 220 indexed citations. Recurring topics across this work include Advanced Text Analysis Techniques (3 papers), Web Data Mining and Analysis (2 papers), Sentiment Analysis and Opinion Mining (2 papers), Consumer Market Behavior and Pricing (2 papers), Stock Market Forecasting Methods (1 paper), Consumer Retail Behavior Studies (1 paper), Data Mining Algorithms and Applications (1 paper) and Topic Modeling (1 paper). The work is most often cited by research in Artificial Intelligence (152 citations), Information Systems (99 citations), Marketing (36 citations), Management Science and Operations Research (23 citations) and Computer Science Applications (6 citations). Marko Krema has collaborated with scholars based in United States and Switzerland. Frequent co-authors include Andrew Fano, Rayid Ghani, Katharina Probst, Yan Liu, Chad Cumby, Sohini Roychowdhury, Brian C. J. Moore, Arijit Mukherjee, Punit Agrawal and Brian R. Moore. Their work appears in journals such as ACM SIGKDD Explorations Newsletter.
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.