The implementation of overlapping clustering (NEO-K-Means)
I have never heard of NEO-k-means. So I wouldn't call it "state of the art": which tools does include it?

Plenty of methods are published every week and have zero impact because they are redundant, badly written, only work on a single data set, hard to parameterize, or outright irreproducible (As I have not read NEO-k-Means, I'm not claiming any of this applies to this particular algorithm!)

Nevertheless, it is not the first to do non-overlapping clustering.


Fuzzy c-means (FCM): a soft-asssignment k-means variant
EM (Gaussian Mixture Modeling) is even more powerful, and has a sound theorertical backing
Subspace and correlation clusterings are usually overlapping, too.


I'd start with GMM and FCM, as these have been successfully used by many people.