such as "Introduction", "Conclusion"..etc
Given two clustering results A and B, for which both
NMI(A,B), NMI(B,A) and LA(A,B) values are high (nearing the maximum
value of 1.0), the two clusterings are very similar, and when all three
are significantly lower, they are very different. But when NMI(A,B) is
high, NMI(B,A) is low and LA is low, then it is likely that A is a
refinement of B. In this case, many clusters in B have been broken into
two or more clusters in A (possible combinations summarized in here)
(1). The magnitude of dissimilarity that is important is defined by the
user and may vary considerably with the dataset, although values
<0.7 for both LA and NMI are usually viewed as quite different.
Additional interpretation of differences measured by LA and NMI depends
on more detailed analysis of the dissimilarities and their distribution
over the dataset, as outlined above.
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