Low-complexity fuzzy relational clustering algorithms for Web mining

By R. Krishnapuram, Anupam Joshi, Olfa Nasraoui, Liyu Yi. IEEE transactions on fuzzy systems, 2001

419 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Information Systems, Signal Processing

View Paper: https://www.semanticscholar.org/paper/9d190d311d0240153bdf6a5d9689659d6803e79b

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Yung-Yu Chuang
2. T. Warren Liao
3. Chu-Song Chen
4. Hsin-Chien Huang
5. Luis Gravano
6. John Paparrizos
7. Kasun Bandara
8. Christoph Bergmeir

In Information Systems

1. T. Warren Liao
2. Chu-Song Chen
3. Ahmet Arslan
4. Rafael Valle
5. Ibrahim Berkan Aydilek
6. Jason Poulos

In Signal Processing

1. Yung-Yu Chuang
2. T. Warren Liao
3. Chu-Song Chen
4. Luis Gravano
5. John Paparrizos
6. Christoph Bergmeir
7. Kasun Bandara
8. Slawek Smyl

Citations in the corpus

• Multiple Kernel Fuzzy Clustering (2012, background): “Krishnapuram et al. [20] presented the fuzzy c-medoid relational clustering algorithm, which can efficiently cluster large datasets.”
• Clustering of time series data - a survey (2005, methodology): “Two counterparts for fuzzy partitions are thefuzzy c-means algorithm[4] and the fuzzy c-medoidsalgorithm [5].”
• Towards Missing Data Imputation: A Study of Fuzzy K-means Clustering Method (2004, background): “where m > 1 is the fuzzifier, and ∑K j=1 U(vj , xi) = 1 for any data object xi (1 ≤ i ≤ N) [7].”