Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies
if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the
same subfield and year (this is the minimum needed to enter the top 1%, not the average
within it), or reaches the top citation threshold in at least one of its specific research
topics.
Graph based anomaly detection and description: a survey
2014878 citationsLeman Akoglu, Hanghang Tong et al.profile →
This map shows the geographic impact of Leman Akoglu'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 Leman Akoglu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Leman Akoglu more than expected).
This network shows the impact of papers produced by Leman Akoglu. 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 Leman Akoglu. The network helps show where Leman Akoglu may publish in the future.
Co-authorship network of co-authors of Leman Akoglu
This figure shows the co-authorship network connecting the top 25 collaborators of Leman Akoglu.
A scholar is included among the top collaborators of Leman Akoglu based on the total number of
citations received by their joint publications. Widths of edges
represent the number of papers authors have co-authored together.
Node borders
signify the number of papers an author published with Leman Akoglu. Leman Akoglu is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Zhang, Sean X., et al.. (2022). Sparx: Distributed Outlier Detection at Scale. Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining. 4530–4540.1 indexed citations
8.
Nguyen, Hung T., et al.. (2021). GAWD. 143–150.6 indexed citations
9.
Zhao, Yue, Ryan A. Rossi, & Leman Akoglu. (2021). Automatic Unsupervised Outlier Model Selection. Neural Information Processing Systems. 34.22 indexed citations
Akoglu, Leman, Emmanuel Müller, & Jilles Vreeken. (2013). Proceedings of the ACM SIGKDD Workshop on Outlier Detection and Description. Knowledge Discovery and Data Mining.17 indexed citations
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.