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.
Efficient algorithms for mining outliers from large data sets
20001.2k citationsRajeev Rastogi, Kyuseok Shim et al.profile →
Rock: A robust clustering algorithm for categorical attributes
2000926 citationsSudipto Guha, Rajeev Rastogi et al.profile →
Efficient algorithms for mining outliers from large data sets
2000780 citationsRajeev Rastogi, Kyuseok Shim et al.profile →
Peers — A (Enhanced Table)
Peers by citation overlap · career bar shows stage (early→late)
cites ·
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This map shows the geographic impact of Kyuseok Shim'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 Kyuseok Shim with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kyuseok Shim more than expected).
This network shows the impact of papers produced by Kyuseok Shim. 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 Kyuseok Shim. The network helps show where Kyuseok Shim may publish in the future.
Co-authorship network of co-authors of Kyuseok Shim
This figure shows the co-authorship network connecting the top 25 collaborators of Kyuseok Shim.
A scholar is included among the top collaborators of Kyuseok Shim 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 Kyuseok Shim. Kyuseok Shim is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Park, Jin Man, et al.. (2012). A breast tumor classification method based on ultrasound BI-RADS data mining. 1–4.1 indexed citations
12.
Lee, Hongrae, Raymond T. Ng, & Kyuseok Shim. (2007). Extending q-grams to estimate selectivity of string matching with low edit distance. Very Large Data Bases. 195–206.38 indexed citations
Guha, Sudipto, Chulyun Kim, & Kyuseok Shim. (2004). XWAVE: optimal and approximate extended wavelets. Very Large Data Bases. 288–299.21 indexed citations
15.
Shim, Kyuseok, et al.. (2003). Proceedings of the 7th Pacific-Asia conference on Advances in knowledge discovery and data mining. Knowledge Discovery and Data Mining.15 indexed citations
16.
Shim, Kyuseok & Ramakrishnan Srikant. (2000). Workshop Report: 1999 ACM SIGMOD Workshop on Research Issues in Data Mining and Knowledge Discovery.. 1. 115–116.1 indexed citations
17.
Shim, Kyuseok. (1999). ROCK: A Clustering Algorithm for Categorical Attributes.5 indexed citations
18.
Garofalakis, Minos, Rajeev Rastogi, & Kyuseok Shim. (1999). SPIRIT: Sequential Pattern Mining with Regular Expression Constraints. Very Large Data Bases. 223–234.263 indexed citations
Agrawal, Rakesh & Kyuseok Shim. (1996). Developing tightly-coupled data mining applications on a relational database system. Knowledge Discovery and Data Mining. 287–290.56 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.