W03-1102 each paragraph to calculate the local clustering score . After obtaining both
W03-1102 each paragraph to calculate the local clustering score . Our approach is reminiscent
W03-1102 Lmax where Lmax is the maximum local clustering score using for normalization
W03-1102 score , and L0 is the normalized local clustering score . The normalized global
W10-4168 solution . Neill ( 2002 ) used local clustering , and determined the senses of
W03-1102 properties . We can consider the local clustering score as the local property of
D14-1031 ) kn ( kn − 1 ) / 2 The local clustering coefficient C ranges between
W03-1102 an algorithm that combines the local clustering score with the global connectivity
E14-3011 network , in terms of average local clustering coefficient ( ¯ C ) and
W03-1102 different views and concepts . The local clustering score only captures the content
W10-0607 as fol - lows : 4 We adopt the local clustering coefficient of Watts and Strogatz
N04-1003 we use the same algorithm : A local clustering is performed to group mentions
W03-1102 paragraph score . Therefore , the local clustering score for paragraph si can be
W13-1732 's word net - work , or as the local clustering coefficient vector of these words
D14-1031 neighbors of a node n is called the local clustering coefficient ( C ) ( Watts and
P05-3020 that for word sense induction the local clustering of local vectors is more appropriate
P06-2050 between characters , and strong local clustering . Moreover , due to its dynamic
E14-3011 Crand and Lrand are the average local clustering coefficient and the average shortest
E14-3011 where C and L are the average local clustering coefficient and the average shortest
W13-1732 neighborhood size ( order 1 ) 4 . local clustering coefficient We take a set of
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