WaveCluster: a wavelet-based clustering approach for spatial data in very large databases
By Gholamhosein Sheikholeslami, Surojit Chatterjee, A. Zhang. The VLDB journal, 2000
310 citations recorded by the source corpus.
Subfields: Artificial Intelligence, Signal Processing
View Paper: https://www.semanticscholar.org/paper/22999b13e8d7f7fb63f773a74f7c02a92824732f
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
- Pedro Contreras
- Fionn Murtagh
- Chin-Teng Lin
- A. Niknafs
- Mukesh Prasad
- Mohamed Hammad
- Meng Joo Er
- Akshansh Gupta
In Signal Processing
- Pedro Contreras
- Fionn Murtagh
- Chin-Teng Lin
- A. Niknafs
- Mohamed Hammad
- Meng Joo Er
- Renée J. Miller
- Wee Keong Ng
Citations in the corpus
- Algorithms for hierarchical clustering: an overview, II (2017, methodology): “• WaveCluster: This clustering technique proposed by Sheikholeslami et al.(63) defines a uniform two-dimensional grid on the data and represents the data points in each cell by the number of points.”
- A survey on data stream clustering and classification (2015, methodology): “and WaveCluster with wavelet transformation method to make the clusters more salient in the transformed space [85].”
- NbClust: An R Package for Determining the Relevant Number of Clusters in a Data Set (2014, background): “More recently, Sheikholeslami, Chatterjee, and Zhang (2000) classified clustering methods into the following types: partitional clustering, hierarchical clustering, density-based clustering and grid based clustering.”
- Similarity search over time-series data using wavelets (2002, background): “How does the number of dimensions or features used in the indexing effect the search performance?”
- Progress in Outlier Detection Techniques: A Survey (2019, methodology): “Grid-based clustering methods: STING [94], Wavecluster [155], DCluster [156] VOLUME 7, 2019 107983 v. Clustering methods for High-Dimensional Data: CLIQUE [157], HPStream [158] In addition to the following algorithms, which have been covered in existing literature [5], [22], [26], [33], a two-phase ”
- A review of clustering techniques and developments (2017, methodology): “Few algorithms, which use hierarchical clustering with some enhancements, are given below: (i) Balanced Iterative Reducing and Clustering Using Hierarchies (BIRCH) BIRCH [131] contains the idea of cluster features (CF).”