Shaul Markovitch

58 papers and 2.2k indexed citations i.

About

Shaul Markovitch is a scholar working on Artificial Intelligence, Computational Theory and Mathematics and Information Systems. According to data from OpenAlex, Shaul Markovitch has authored 58 papers receiving a total of 2.2k indexed citations (citations by other indexed papers that have themselves been cited), including 55 papers in Artificial Intelligence, 10 papers in Computational Theory and Mathematics and 7 papers in Information Systems. Recurrent topics in Shaul Markovitch’s work include Machine Learning and Algorithms (15 papers), Topic Modeling (15 papers) and Machine Learning and Data Classification (11 papers). Shaul Markovitch is often cited by papers focused on Machine Learning and Algorithms (15 papers), Topic Modeling (15 papers) and Machine Learning and Data Classification (11 papers). Shaul Markovitch collaborates with scholars based in Israel, United States and United Kingdom. Shaul Markovitch's co-authors include Evgeniy Gabrilovich, David Carmel, Michael Lindenbaum, Ido Dagan, Paul D. Scott, Kira Radinsky, Erez Karpas, Omer Levy, Ikuya Yamada and Carmel Domshlak and has published in prestigious journals such as Artificial Intelligence, Machine Learning and Journal of Machine Learning Research.

In The Last Decade

Co-authorship network of co-authors of Shaul Markovitch i

Fields of papers citing papers by Shaul Markovitch

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Countries citing papers authored by Shaul Markovitch

Since Specialization
Citations

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

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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