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Data Knowledge Extraction

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It is the means to extract knowledge from the raw data. One of the biggest challenges in big data and machine learning is the creation of value out of the raw data. When dealing with personal data, this must be coupled with privacy preserving approaches, so that only the necessary data is disclosed, and the data owner keeps the control on it.

It is the means to extract knowledge from the raw data. One of the biggest challenges in big data and machine learning is the creation of value out of the raw data. When dealing with personal data, this must be coupled with privacy preserving approaches, so that only the necessary data is disclosed, and the data owner keeps the control on it.

The DKE consists of machine learning approaches to aggregate data, abstract models to predict future data (e.g., predict user’s interest in recommendation systems), fuse data coming from different source to derive generic suggestions (e.g., to support decision by users, providing suggestions based on decisions taken by users with similar interest).