W06-1649 labeled data was used to guide the semi-supervised clustering on XL+U . Firstly , the labeled
S07-1069 accurate . Therefore , we apply semi-supervised clustering to disambiguate personal names
S07-1069 search-result Web pages . Our semi-supervised clustering approach is characterized by
D09-1091 of data points to clusters . In semi-supervised clustering , prior knowledge is given to
S07-1069 agglomerative clustering and our proposed semi-supervised clustering , respectively . " Set 1 , "
E14-1029 clustering , and then perform semi-supervised clustering . This way the provided labels
S07-1069 search results , we introduce semi-supervised clustering that uses the seed page to aid
P06-2030 during clustering . Our goal for semi-supervised clustering is to classify negative stories
W06-1640 differs substantially from that of semi-supervised clustering . We propose an algorithm for
S07-1069 and then describe our proposed semi-supervised clustering approach . In the following discussion
E14-1029 et al. , 2004 ) also known as semi-supervised clustering is a recent development in the
P06-2030 Bilingual Comparable Corpora and Semi-supervised Clustering for Topic Tracking </title> Fumiyo
S07-1069 value of purity , our proposed semi-supervised clustering outperforms agglomerative clustering
S07-1069 clustering outperforms our proposed semi-supervised clustering by 0.21 in the value of purity
S07-1069 semisupervised clustering . In our semi-supervised clustering approach , we use the following
W06-1649 1991 ) as distance measure for semi-supervised clustering and ELP , since plain LP with
W10-2802 probabilistic generative model for semi-supervised clustering , providing a principled framework
S07-1069 : Web People Search Task Using Semi-Supervised Clustering Approach </title> Kazunari Sugiyama
S07-1069 respectively . 3.2 Our Proposed Semi-supervised Clustering As described in Section 1 , if
D09-1091 hypertext classification problem . Semi-supervised clustering enhances clustering task by incorporating
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