Markus Schaal

516 citations
13 papers · 252 · h-index 6

Impact in

  • Marketing top 10%
    • Customer churn and segmentation
    • Consumer Retail Behavior Studies
    • Recommender Systems and Techniques

Papers in

Markus Schaal

10 papers receiving 243 citations

Peers

Markus Schaal
Comparison fields: 5 of 59
  • Marketing 55
  • Information Systems 115
  • Artificial Intelligence 129
  • Information Systems and Management 25
  • Computational Mathematics 2
Replace Frank E. Walter with:
Frank E. Walter Switzerland
Narisa Zhao China
Inma Garcia Spain
Zeshan Fayyaz Canada
Yanzan Zhou United States
Bogdan Walek Czechia
Allison J. B. Chaney United States
Uri Hanani Israel
Surya Kallumadi United States
Grant Williams United States
Markus Schaal relative to Frank E. Walter Switzerland Frank E. Walter's profile →
Citations per field
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Citations per year

Countries citing papers authored by Markus Schaal

Since Specialization
Citations

This map shows the geographic impact of Markus Schaal'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 Markus Schaal with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Markus Schaal more than expected).

Fields of papers citing papers by Markus Schaal

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Markus Schaal. 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 Markus Schaal. The network helps show where Markus Schaal may publish in the future.

Co-authors

The 9 scholars most cited alongside Markus Schaal, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Markus Schaal Line = papers co-authored together Markus Schaal links everyone, so they are left out of the graph.

All Works

13 of 13 papers shown
#Work
1 2020106
2 201547
3 201339
4
Topic extraction from online reviews for classification and recommendation
201335
5 20129
6 20128
7 20083
8 20102
9 20132
10 20121
11
WrapIt: Automated Integration of Web Databases with Extensional Overlaps
20020
12 20000
13 20070

About Markus Schaal

Markus Schaal is a scholar working on Artificial Intelligence, Information Systems, Communication, Computer Vision and Pattern Recognition and Computer Networks and Communications, having authored 13 papers that have together received 252 indexed citations. Recurring topics across this work include Advanced Text Analysis Techniques (4 papers), Topic Modeling (4 papers), Sentiment Analysis and Opinion Mining (3 papers), Web Data Mining and Analysis (2 papers), Wikis in Education and Collaboration (2 papers), Semantic Web and Ontologies (2 papers), Hermeneutics and Narrative Identity (1 paper) and Big Data and Business Intelligence (1 paper). The work is most often cited by research in Marketing (55 citations), Information Systems (115 citations), Artificial Intelligence (129 citations), Information Systems and Management (25 citations) and Computational Mathematics (2 citations). Markus Schaal has collaborated with scholars based in Ireland, Türkiye and Netherlands. Frequent co-authors include Stefan Lessmann, Barry Smyth, Michael P. O’Mahony, Ruihai Dong, Kevin McCarthy, Roland M. Mueller, Hayrettin Gürkök, Roland Müller and Rachael Rafter. Their work appears in journals such as The Learning Organization, Expert Systems with Applications, Journal of Intelligent Information Systems, Refubium (Universitätsbibliothek der Freien Universität Berlin) and Research Repository UCD (University College Dublin).

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.

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