青云翻译

Dong Jun, who in [39] proposed a variable similarity metric affine propagation clustering algorithm, for close and partially overlapping data sets, can give better clustering results, but the algorithm in the density uneven or loose data sets can not get the desired results.

Dong Jun and the others in the literature [39] presented in variable similarity measurement of affinity propagation clustering algorithm, for relatively close and overlapping data sets, may give a better clustering of results, but comparison algorithm in non-uniform density or unable to get the desi

Dong Jun et al. proposed in literature (39) invariable similar measure affine dissemination cluster algorithm, regarding quite close and part overlap data set, may give the good cluster result, but the algorithm non-uniform or in the quite loose data set cannot obtain the ideal result in the density

Mr Tung Chee Hwa, and others in the literature [ 39] proposed a similarity of variable metric affine communications clustering algorithm, for the more closely and partially overlapping set of data, can be given a better clustering algorithm results in density, but is not uniform or is a loose set of

Dong Jun and the others in the literature [39] presented in variable similarity measurement of affinity propagation clustering algorithm, for relatively close and overlapping data sets, may give a better clustering of results, but comparison algorithm in non-uniform density or unable to get the desi