fastcluster: Fast Hierarchical, Agglomerative Clustering Routines for R and Python by Daniel Müllner.
Abstract:
The fastcluster package is a C++ library for hierarchical, agglomerative clustering. It provides a fast implementation of the most efficient, current algorithms when the input is a dissimilarity index. Moreover, it features memory-saving routines for hierarchical clustering of vector data. It improves both asymptotic time complexity (in most cases) and practical performance (in all cases) compared to the existing implementations in standard software: several R packages, MATLAB, Mathematica, Python with SciPy.
Builds upon the author’s prior work: Modern hierarchical, agglomerative clustering algorithms.
Both papers are worth your time or you can cut to the chase with the packages you will find here.
When you stop to think about it, merging (as in topic maps) is just clustering followed by processing of members of the cluster.
Which should open merging up to the use of any number of clustering algorithms, depending upon what subjects you want to talk about.