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Semi-supervised structuring of complex data

Rizoiu, Marian-Andrei

Description

The objective of the thesis is to explore how complex data can be treated using unsupervised machine learning techniques, in which additional information is injected to guide the exploratory process. Starting from specific problems, our contributions take into account the different dimensions of the complex data: their nature (image, text), the additional information attached to the data (labels, structure, concept ontologies) and the temporal dimension. A special attention is given to data...[Show more]

CollectionsANU Research Publications
Date published: 2013
Type: Conference paper
URI: http://hdl.handle.net/1885/154181
Source: IJCAI International Joint Conference on Artificial Intelligence
Access Rights: Open Access

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