Size and complexity of data repositories collaboratively created by Web users generate a need for new processing approaches. In this paper, we study the problem of detection of fine-grained communities of users in social networks, which can be defined as clustering with a large number of clusters

Filename	Size	Update
main2.m	1086	2017-10-18
sqdist.m	152	2017-07-01
stdv.m	156	2014-02-12
stream.m	560	2017-07-01
Untitled2.m	1609	2016-11-29
Untitled5.m	4035	2017-02-04
usps38.mat	171193	2014-02-12
apriori.m	695	2017-07-01
eff.m	583	2017-07-01
FpGrowth.m	729	2017-07-01
INys.m	664	2017-07-01
main.m	15423	2017-07-20
G.txt	32900	2017-12-11
Iter.txt	2	2017-12-11
K.txt	2	2017-12-11
test.txt	18	2017-12-11
VV1.txt	0	2017-12-11
000b.mat	54059	2014-02-15
000c.mat	13363	2014-02-17
000d.mat	17307	2014-02-17
CDTB01.mat	9222	2014-03-11
CDTBDemo01.m	273	2013-12-09
CDTBDemo02.m	549	2014-02-17
CheckAll01.m	2947	2014-02-16
CheckAll02.m	2947	2014-02-16
CheckAll03.m	2969	2014-02-16
ClustExp.m	1486	2017-12-11

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