Clustering categorical data: an approach based on dynamical systems
By David Gibson, Jon M. Kleinberg, Prabhakar Raghavan. The VLDB journal, 2000
476 citations recorded by the source corpus.
Subfields: Artificial Intelligence, Computer Vision and Pattern Recognition, Signal Processing
View Paper: https://www.semanticscholar.org/paper/548a22394a60661f057979855e82465b6ebaee68
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
- Charu C. Aggarwal
- Dacheng Tao
- Bernhard Schölkopf
- Pavel Berkhin
- Dengyong Zhou
- Serge J. Belongie
- Petros Drineas
- Santosh Srinivas Vempala
In Computer Vision and Pattern Recognition
- Charu C. Aggarwal
- Bernhard Schölkopf
- Luc Van Gool
- Dacheng Tao
- Xiaogang Wang
- Jitendra Malik
- Ming-Hsuan Yang
- Andrea Vedaldi
In Signal Processing
- Pavel Berkhin
- Charu C. Aggarwal
- Bernhard Schölkopf
- Chengxiang Zhai
- Santosh Srinivas Vempala
- Petros Drineas
- Kristin Branson
- Dengyong Zhou
Citations in the corpus
- Learning with Hypergraphs: Clustering, Classification, and Embedding (2006, methodology): “There have actually existed a large amount of literature on hypergraph partitioning, which arises from a variety of practical problems, such as partitioning circuit netlists [11], clustering categorial data [9], and image segmentation [1].”
- Outlier Analysis (2013, background): “The earliest work on categorical outlier detection was performed in the context of clustering algorithms [176, 186, 189, 232, 255].”
- A Survey of Clustering Data Mining Techniques (2006, methodology): “The algorithm STIRR (Sieving Through Iterated Reinfircement) [92] deals with co-occurrence phenomenon for d-dimensional categorical objects, tuples.”
- A Survey of Text Clustering Algorithms (2012, background): “The problem has also been studied for the case of categorical data [10] [41] [43], in which the attributes may take on nominal values.”
- Similarity Measures for Categorical Data: A Comparative Evaluation (2008, unknown): “• Number of attributes, d.”
- Clustering Large Graphs via the Singular Value Decomposition (2004, methodology): “We should note here that these aspects of clustering in the context of the web graph, as well as the introduction of the SVD technique to cluster such graphs was pioneered in Kleinberg (1998) (see also Gibson, Kleinberg, & Raghavan, 1998 ).”
- Higher order learning with graphs (2006, background): “In (Gibson et al., 1998) the authors have proposed a dynamical system to cluster categorical data that can be represented using a hypergraph.”