Abstract: Classifying data hierarchically is an efficient approach
to analyze data. Data is usually classified into multiple categories, or
annotated with a set of labels. To analyze multi-labeled data, such
data must be specified by giving a set of labels as a semantic range.
There are some certain purposes to analyze data. This paper shows
which multi-labeled data should be the target to be analyzed for
those purposes, and discusses the role of a label against a set of
labels by investigating the change when a label is added to the set of
labels. These discussions give the methods for the advanced analysis
of multi-labeled data, which are based on the role of a label against
a semantic range.
Abstract: Collected data must be organized to be utilized efficiently, and hierarchical classification of data is efficient approach to organize data. When data is classified to multiple categories or annotated with a set of labels, users request multi-labeled data by giving a set of labels. There are several interpretations of the data expressed by a set of labels. This paper discusses which data is expressed by a set of labels by introducing orders for sets of labels and shows that there are four types of orders, which are characterized by whether the labels of expressed data includes every label of the given set of labels within the range of the set. Desirable properties of the orders, data is also expressed by the higher set of labels and different sets of labels express different data, are discussed for the orders.