Analyzing multi-labeled data based on the roll of a concept against a semantic range

Masahiro Kuzunishi, Tetsuya Furukawa, Ke Lu

Research output: Contribution to journalArticle

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.

Original languageEnglish
Pages (from-to)974-980
Number of pages7
JournalWorld Academy of Science, Engineering and Technology
Volume46
Publication statusPublished - 2010

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Semantics

All Science Journal Classification (ASJC) codes

  • Engineering(all)

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Analyzing multi-labeled data based on the roll of a concept against a semantic range. / Kuzunishi, Masahiro; Furukawa, Tetsuya; Lu, Ke.

In: World Academy of Science, Engineering and Technology, Vol. 46, 2010, p. 974-980.

Research output: Contribution to journalArticle

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