Transductive learning from textual data with relevant example selection
DEXA'10 Proceedings of the 21st international conference on Database and expert systems applications: Part II
A survey of hierarchical classification across different application domains
Data Mining and Knowledge Discovery
Personalized mode transductive spanning SVM classification tree
Information Sciences: an International Journal
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Transductive learning is the learning setting that permits to learn from "particular to particular'' and to consider both labelled and unlabelled examples when taking classification decisions. In this paper, we investigate the use of transductive learning in the context of hierarchical text categorization. At this aim, we exploit a modified version of an inductive hierarchical learning framework that permits to classify documents in internal and leaf nodes of a hierarchy of categories. Experimental results on real world datasets are reported.