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One Class Clustering in the Text Domain

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Figure

Figure 1: The problem of hyperspherical decision bound-aries in one-class models for text, as projected on 2D:(left) a too small portion of the core is captured; (right)too much space around the core is captured.
Figure 3: (left) Words’ pq ( w ( w ) values when sorted by their ) values; (right) words’( ρ w ) values.
Table 1: One-class clustering accuracy of our OCCC andLTB models on the WAD and the TW detection tasks, ascompared to OC-SVM and OC-RD
Figure 5: Web appearance disambiguation: F-measureas a function of document cluster size: a vertical line in-dicates the point where precision equals recall (and there-fore equals accuracy)
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