ACM Transactions on Knowledge Discovery from Data

1.1k papers and 22.5k indexed citations i.

About

The 1.1k papers published in ACM Transactions on Knowledge Discovery from Data in the last decades have received a total of 22.5k indexed citations. Papers published in ACM Transactions on Knowledge Discovery from Data usually cover Artificial Intelligence (740 papers), Statistical and Nonlinear Physics (281 papers) and Information Systems (275 papers) specifically the topics of Complex Network Analysis Techniques (277 papers), Advanced Graph Neural Networks (214 papers) and Topic Modeling (124 papers). The most active scholars publishing in ACM Transactions on Knowledge Discovery from Data are Jure Leskovec, Christos Faloutsos, Zhi‐Hua Zhou, Jon Kleinberg, Yehuda Koren, Daniel Kifer, Ashwin Machanavajjhala, Muthuramakrishnan Venkitasubramaniam, Johannes Gehrke and Kai Ming Ting.

In The Last Decade

Fields of papers published in ACM Transactions on Knowledge Discovery from Data

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers published in ACM Transactions on Knowledge Discovery from Data. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers published in ACM Transactions on Knowledge Discovery from Data.

Countries where authors publish in ACM Transactions on Knowledge Discovery from Data

Since Specialization
Citations

This map shows the geographic impact of research published in ACM Transactions on Knowledge Discovery from Data. 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 papers published in ACM Transactions on Knowledge Discovery from Data with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites ACM Transactions on Knowledge Discovery from Data 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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