Massive data processing for effective trustworthiness modeling
Abstract
This chapter focuses on the issue of handling user trustworthiness information, which involves large amounts of ill-structured data generated by various systems during learning activities. Processing this information is computationally costly, especially if required in real time. The chapter discusses and proposes a parallel processing approach for building relevant information modeling trustworthiness levels for e-Learning to support various intensive learning activities even in real time. In particular, the methods and techniques presented here involve the step of data processing within the knowledge management process in trustworthiness and security methodology ...
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