Micheline Kamber

34.5k total citations · 3 hit papers
20 papers, 15.0k citations indexed

About

Micheline Kamber is a scholar working on Information Systems, Artificial Intelligence and Computational Theory and Mathematics. According to data from OpenAlex, Micheline Kamber has authored 20 papers receiving a total of 15.0k indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Information Systems, 7 papers in Artificial Intelligence and 5 papers in Computational Theory and Mathematics. Recurrent topics in Micheline Kamber's work include Data Mining Algorithms and Applications (9 papers), Rough Sets and Fuzzy Logic (5 papers) and Data Management and Algorithms (4 papers). Micheline Kamber is often cited by papers focused on Data Mining Algorithms and Applications (9 papers), Rough Sets and Fuzzy Logic (5 papers) and Data Management and Algorithms (4 papers). Micheline Kamber collaborates with scholars based in Canada and United States. Micheline Kamber's co-authors include Jiawei Han, Jiawei Han, Jian Pei, Jenny Y. Chiang, Alan C. Evans, D. Louis Collins, G. Francis, Rajjan Shinghal, Shan Cheng and Yilong Ma and has published in prestigious journals such as IEEE Transactions on Medical Imaging, Computerized Medical Imaging and Graphics and Choice Reviews Online.

In The Last Decade

Micheline Kamber

19 papers receiving 13.3k citations

Hit Papers

Data mining: concepts and techniques 2006 2026 2012 2019 2012 2006 2021 4.0k 8.0k 12.0k

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Micheline Kamber Canada 15 7.0k 5.5k 2.1k 1.8k 1.8k 20 15.0k
Lior Rokach Israel 51 7.2k 1.0× 4.1k 0.7× 2.3k 1.1× 2.1k 1.2× 2.1k 1.2× 283 16.7k
Padhraic Smyth United States 62 8.3k 1.2× 4.6k 0.8× 2.8k 1.4× 1.6k 0.9× 1.9k 1.1× 271 17.6k
Ron Kohavi United States 36 9.6k 1.4× 4.2k 0.8× 1.8k 0.9× 1.6k 0.9× 3.6k 2.1× 66 21.8k
Mark A. Hall United States 39 5.5k 0.8× 3.3k 0.6× 1.2k 0.6× 1.2k 0.7× 1.3k 0.8× 292 20.5k
Mark Hall United Kingdom 20 7.8k 1.1× 3.5k 0.7× 2.1k 1.0× 2.0k 1.1× 2.8k 1.6× 88 18.8k
Usama M. Fayyad United States 36 6.0k 0.9× 4.0k 0.7× 2.1k 1.0× 1.2k 0.7× 1.7k 0.9× 100 11.1k
Geoffrey Holmes New Zealand 37 11.3k 1.6× 4.4k 0.8× 2.7k 1.3× 2.6k 1.4× 3.1k 1.7× 127 23.0k
Bernhard Pfahringer New Zealand 33 10.5k 1.5× 3.8k 0.7× 2.5k 1.2× 2.4k 1.3× 2.7k 1.5× 128 18.6k
Eric Horvitz United States 73 8.0k 1.2× 4.1k 0.8× 1.2k 0.6× 1.7k 0.9× 3.0k 1.7× 393 20.5k
W. Philip Kegelmeyer United States 15 11.5k 1.7× 2.6k 0.5× 1.4k 0.7× 1.5k 0.8× 2.3k 1.3× 38 21.7k

Countries citing papers authored by Micheline Kamber

Since Specialization
Citations

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

Fields of papers citing papers by Micheline Kamber

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Micheline Kamber

This figure shows the co-authorship network connecting the top 25 collaborators of Micheline Kamber. A scholar is included among the top collaborators of Micheline Kamber 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 Micheline Kamber. Micheline Kamber is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Han, Jiawei, Micheline Kamber, & Jian Pei. (2021). Data Mining Concepts and Techniques Third Edition. TU Digital Collections (Thammasat University). 219 indexed citations breakdown →
2.
Han, Jiawei, Micheline Kamber, & Jian Pei. (2014). Data Mining : Concepts and Techniques -3/Ed.. 17 indexed citations
3.
Han, Jiawei, Micheline Kamber, & Jian Pei. (2012). 2012- Data Mining. Concepts and Techniques, 3rd Edition.pdf. 102 indexed citations
4.
Han, Jiawei & Micheline Kamber. (2012). Data mining: concepts and techniques. Choice Reviews Online. 49(6). 49–3305. 13447 indexed citations breakdown →
5.
Han, Jiawei, Micheline Kamber, & Jian Pei. (2011). Data Mining : Concepts and Techniques 3rd edition Ed. 3. Elsevier eBooks. 60 indexed citations
6.
Han, Jiawei, Micheline Kamber, & Ari Visa. (2010). Data Mining: Concepts and Techniques — Slides for Textbook — — Chapter 2 —. 3 indexed citations
7.
Chakrabarti, Soumen, Earl Cox, Eibe Frank, et al.. (2008). Data Mining: Know It All. CERN Document Server (European Organization for Nuclear Research). 43 indexed citations
8.
Han, Jiawei & Micheline Kamber. (2006). Data Mining: Concepts and Techniques (2nd edition). 627 indexed citations breakdown →
9.
Kamber, Micheline, et al.. (2002). Using Data Cubes for Metarule-Guided Mining of Multi-Dimensional Association Rules. 8 indexed citations
11.
Kamber, Micheline, et al.. (2002). Generalization and decision tree induction: efficient classification in data mining. 111–120. 59 indexed citations
12.
Han, Jiawei, Jenny Y. Chiang, Jianping Chen, et al.. (1997). DBMiner: a system for data mining in relational databases and data warehouses. Conference of the Centre for Advanced Studies on Collaborative Research. 8. 34 indexed citations
13.
Kamber, Micheline, Jiawei Han, & Jenny Y. Chiang. (1997). Metarule-Guided Mining of Multi-Dimensional Association RulesUsing Data Cubes. Knowledge Discovery and Data Mining. 207–210. 138 indexed citations
14.
Kamber, Micheline & Rajjan Shinghal. (1996). Evaluating the interestingness of characteristic rules. Knowledge Discovery and Data Mining. 263–266. 54 indexed citations
15.
Kamber, Micheline & Rajjan Shinghal. (1996). Proposed interestingness measure for characteristic rules. National Conference on Artificial Intelligence. 1393–1393. 3 indexed citations
16.
Kamber, Micheline, et al.. (1995). Model-based 3-D segmentation of multiple sclerosis lesions in magnetic resonance brain images. IEEE Transactions on Medical Imaging. 14(3). 442–453. 156 indexed citations
17.
Kamber, Micheline, Rajjan Shinghal, D. Louis Collins, Gordon Francis, & Alan C. Evans. (1995). Model-Based 3-D Segmentation of Multiple Sclerosis Lesions in Magnetic Resonance Brain. 7 indexed citations
18.
Ma, Yilong, Micheline Kamber, & Alan C. Evans. (1993). 3D simulation of pet brain images using segmented MRI data and positron tomograph characteristics. Computerized Medical Imaging and Graphics. 17(4-5). 365–371. 20 indexed citations
19.
Rousset, Olivier, Yilong Ma, Micheline Kamber, & Alan C. Evans. (1993). 3D simulations of radiotracer uptake in deep nuclei of human brain. Computerized Medical Imaging and Graphics. 17(4-5). 373–379. 14 indexed citations
20.
Kamber, Micheline, D. Louis Collins, Rajjan Shinghal, G. Francis, & Alan C. Evans. (1992). <title>Model-based 3-D segmentation of multiple sclerosis lesions in dual-echo MRI data</title>. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 1808. 590–600. 18 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.

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