WaveCluster: A Multi-Resolution Clustering Approach for Very Large Spatial Databases

Summary: WaveCluster uses wavelet-based multi-resolution clustering for very large spatial databases. It detects arbitrarily shaped clusters, is robust to noise and input order, and offers scalable, efficient performance versus recent methods. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID: 8508
Venue: VLDB
Year: 1998
Pagerank: 0.00011464884
Overall Rank: 1,538 | 89.31%
DOI: -

Incoming Non-self Citations Over Time

Authors

Incoming Citations (Sorted by Pagerank)

Showing 6 of 6 citing papers.

Rank	Citing Paper	Year	Venue	Pagerank
161	LOF: Identifying Density-Based Local Outliers	2000	SIGMOD	0.00039846974
270	OPTICS: Ordering Points To Identify the Clustering Structure	1999	SIGMOD	0.00029505642
3,475	Optimal Grid-Clustering: Towards Breaking the Curse of Dimensionality in High-Dimensional Clustering	1999	VLDB	7.0614822e-05
6,653	Supporting Ranking and Clustering as Generalized Order-By and Group-By	2007	SIGMOD	4.9735307e-05
7,965	PARAgrab: A Comprehensive Architecture for Web Image Management and Multimodal Querying	2006	VLDB	4.613363e-05
12,622	A Shrinking-Based Approach for Multi-Dimensional Data Analysis	2003	VLDB	4.1945683e-05

Outgoing Citations (Sorted by Pagerank)

Showing 3 of 3 cited papers.

Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

Rank	Cited Paper	Year	Venue	Pagerank
27	Efficient and Effective Clustering Methods for Spatial Data Mining	1994	VLDB	0.00080736878
33	BIRCH: An Efficient Data Clustering Method for Very Large Databases	1996	SIGMOD	0.00077324389
1,097	STING : A Statistical Information Grid Approach to Spatial Data Mining	1997	VLDB	0.00014119975

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