HIERDENC
Clustering of categorical data sets with locality-sensitive hashing
...The clustering is achieved via a locality-sensitive hashing of categorical datasets for speed and scalability.
The locality-sensitive hashing method implemented is described in the video lectures under www.mmds.org (Chapter 3).
Information needed for LSH, such as shingles/tokens, MinHash signatures, band hashes to buckets
are stored in several database tables.
Information needed for clustering purposes, such as the most significant pairwise object similarities and density-based similarities are also stored in tables.
An early version of the fast database-based retrieval of nearest neighbors and clustering in large categorical datasets was published in:
Bill Andreopoulos, Aijun An, Xiaogang Wang, Dirk Labudde. ...