Huda, you gave kmeans two points and asked it to cluster them into two clusters. It has assigned the first point to cluster 1, whose centroid is at the first point, and similarly for the second point. Presumably that is not very informative.
I don't know what your data mean, or whether kmeans makes sense, but your description sounds like something more suited to distance-based methods such as hierarchical clustering or multidimensional scaling, both of which are available in the Statistics Toolbox. You would, of course, have to convert your similarities to dissimilarities.
Best Answer