TrustRec: An effective approach to exploit implicit trust and distrust relationships along with explicitones for accurate recommendations

Trust and Distrust: New Relationships and Realities

We propose a new theoretical framework for understanding simultaneous trust and distrust within relationships. grounded in assumptions of multidimensionality and the inherent tensions of relationships. and we separate this research from prior work grounded in assumptions of unidimensionality and balance. Drawing foundational support for this new framework from recent research on simultaneous po...

Matrix Factorization with Explicit Trust and Distrust Relationships

With the advent of online social networks, recommender systems have became crucial for the success of many online applications/services due to their significance role in tailoring these applications to user-specific needs or preferences. Despite their increasing popularity, in general recommender systems suffer from the data sparsity and the cold-start problems. To alleviate these issues, in re...

A Fuzzy Approach to Reasoning with Trust, Distrust and Insufficient Trust

Multi-agent systems are based upon cooperative interactions between agents, in which agents provide information, resources and services to others. Typically agents are autonomous and self-interested, meaning that they have control over their own actions, and that they seek to maximise their own goal achievement, rather than necessarily acting in a benevolent or socially-oriented manner. Consequ...

Trust, Distrust, and Power

a benchmarking approach to optimal asset allocation for insurers and pension funds

uncertainty in the financial market will be driven by underlying brownian motions, while the assets are assumed to be general stochastic processes adapted to the filtration of the brownian motions. the goal of this study is to calculate the accumulated wealth in order to optimize the expected terminal value using a suitable utility function. this thesis introduced the lim-wong’s benchmark fun...