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In this paper, we introduce the main concepts of a new maximum livelihood evidential reasoning (MAKER) framework for data-driven inferential modelling and decision making under different types of uncertainty. It consists of two types of model: state space model (SSM) and evidence space model (ESM), driven by the data that reflects the relationships between system inputs and output. SSM is constructed...
The traditional duplicate bug reports detection approaches are usually based on vector space model. However, the experimental result is rarely satisfying since this method cannot distinguish semantic correlation among bug reports which written by natural languages. Topic model, as a method to model underlying topics of texts, can solve the problem of document similarity calculation methods used in...
Peer to peer (P2P) systems are extremely vulnerable to Sybil attacks, in which a malicious user controls a large number of Sybil peers to collude to break the system laws. This paper proposes a distributed algorithm, named Sybil Resisting Network Clustering (SRNC), to resist the Sybil attack by preventing honest peers from communicating with Sybil Peers. SRNC is based on a social network model. In...
A belief rule-base inference methodology using the evidential reasoning approach (RIMER) has been developed recently, where a new belief rule representation scheme is proposed to extend traditional IF-THEN rules. The belief rule expression matrix in RIMER provides a compact framework for representing expert knowledge. However, it is difficult to accurately determine the parameters of a belief rule...
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