2010 | OriginalPaper | Buchkapitel
Mining Multi-label Data
verfasst von : Grigorios Tsoumakas, Ioannis Katakis, Ioannis Vlahavas
Erschienen in: Data Mining and Knowledge Discovery Handbook
Verlag: Springer US
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A large body of research in supervised learning deals with the analysis of
single-label
data, where training examples are associated with a single label λ from a set of disjoint labels
L
. However, training examples in several application domains are often associated with a
set
of labels
Y ⊆ L
. Such data are called
multi-label
.
Textual data, such as documents and web pages, are frequently annotated with more than a single label. For example, a news article concerning the reactions of the Christian church to the release of the “Da Vinci Code” film can be labeled as both
religion
and
movies
. The categorization of textual data is perhaps the dominant multi-label application.