Abstract
The importance of data mining methods has increased dramatically in recent years, making this research area relevant and challenging to extract actionable knowledge from complex data. Indeed, new algorithms and machine learning methods are constantly being explored to deal with domains that present multiple challenges including high-dimensionality, heterogeneity of features, and complex relationships between data objects. This special issue aims at discussing emerging approaches for learning from complex data, including text data, images, and social media data.
Highlights
Though the crucial role of data mining for knowledge discovery has long been recognized [1], this research area is experiencing a new and explosive growth, due to the exponential increase of the amount of data, as well as to the increasing complexity of these data
This special issue aims at discussing emerging approaches for learning from complex data, including text data, images, and social media data
A number of proposals from this fast-evolving research area are discussed in our special issue on “Advanced Learning Methods for Complex Data”, with a special focus on approaches that exploit semantic information when dealing with complex data and learning from them
Summary
Though the crucial role of data mining for knowledge discovery has long been recognized [1], this research area is experiencing a new and explosive growth, due to the exponential increase of the amount of data, as well as to the increasing complexity of these data. Abstract: The importance of data mining methods has increased dramatically in recent years, making this research area relevant and challenging to extract actionable knowledge from complex data.
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