In this article, we propose a novel super‐agent‐based framework for reputation management and community formation in decentralized systems. We describe this framework in the context of Web service selection where agents with more capabilities act as super‐agents. These super‐agents serve as reputation managers to maintain reputation information of services and share the information with other consumer agents that have fewer capabilities than the super‐agents. In addition, super‐agents can maintain communities and build community‐based reputation for a service based on the opinions from all community members that have similar interests and judgement criteria as the super‐agents or the other community members. A practical reward mechanism is also introduced to create incentives for super‐agents to contribute their resources (to maintain reputation and form communities) and provide truthful reputation information. Experimental results obtained through simulation confirm that our approach achieves better effectiveness and scalability compared to the systems that do not use super‐agents and that do not form communities.

Topic model can project documents into a topic space which facilitates effective document clustering. Selecting a good topic model and improving clustering performance are two highly correlated problems for topic based document clustering. In this paper, we propose a three-phase approach to topic based document clustering. In the first phase, we determine the best topic model and present a formal concept about significance degree of topics and some topic selection criteria, through which we can find the best number of the most suitable topics from the original topic model discovered by LDA. Then, we choose the initial clustering centers by using the k-means++ algorithm. In the third phase, we take the obtained initial clustering centers and use the k-means algorithm for document clustering. Three clustering solutions based on the three phase approach are used for document clustering. The related experiments of the three solutions are made for comparing and illustrating the effectiveness and efficiency of our approach. (C) 2014 Elsevier Ltd. All rights reserved.

Reputation management is an effective way for agents to find good partners to interact with. In this paper, we propose a novel super-agent based reputation mechanism in decentralized systems. We describe it in the context of web service selection where super-agents with more capabilities maintain reputation information of services and share the information with other consumer agents in the system. A practical reward mechanism is also introduced to create incentives for super-agents to contribute their resources and provide truthful reputation information. We carry out experiments to validate our approach based on a simulated web service environment. The experimental results confirm that our super-agent based reputation management achieves better effectiveness compared to the system that does not use super-agents. The reward mechanism also provides strong support for our super-agent based approach.

In this paper, we propose a novel community-based approach for web service selection where super-agents with more capabilities serve as community managers. They maintain communities and build community-based reputation for a service based on the opinions from all community members that have similar interests and judgement criteria. The community-based reputation is useful for consumer agents in selecting satisfactory services when they do not have much personal experience with the services. Experimental results show that our approach results in more effective service selection. A practical reward mechanism is also introduced to create incentives for super-agents to contribute their resources and provide truthful community-based reputation information, as strong support for our approach.

In this paper, we propose a mechanism of using super consumers to manage reputation. Super consumers are consumers with more capabilities, such as cpu power, storage and bandwidth. Super consumers can serve as reputation managers to build global reputation for a service based on the opinions from all the members in the system. Super consumers can also build community-based reputation for a service, by forming their own communities based on similar interests and judgement criteria. Our experiments show that the system using both global and community-based reputation can perform better than the system using just global reputation.

A trust and reputation mechanism is a mechanism using consumers' feedbacks to identify good services from bad ones. Compared with other approaches, it has more advantages in solving the selection problem for web services. The paper proposes a typology to classify trust and reputation systems using the three criteria, centralized or decentralized, person or resource, global or personalized. Inspired by the criteria, some potential research directions for web service selection are pointed out.

Using trust and reputation mechanisms offers a promising way to solve the web service selection problem. The investigation of trust and reputation systems in other areas can provide valuable observations and approaches that can be used in web service systems. Therefore, this paper presents a systematic review of various trust and reputation systems and proposes a typology to classify them from three aspects, centralized vs. decentralized, persons/agents vs. resources, global vs. personalized. These aspects are important not only in that they clarify the difference between various existing trust and reputation systems, but also in that they point out the potential research directions for using trust and reputation in web services and provide some reference systems for them.

A trust and reputation mechanism is a mechanism using consumers' feedbacks to identify good services from bad ones. Compared with other approaches, it has more advantages in solving the selection problem for web services. The paper proposes a typology to classify trust and reputation systems using the three criteria, centralized or decentralized, person or resource, global or personalized. Inspired by the criteria, some potential research directions for web service selection are pointed out.

In this paper, we propose a Bayesian network-based trust model in peer-to-peer networks. Since trust is multi-faceted, even in the same context, peers still need to develop differentiated trust in different aspects of other peers’ behaviors. The peer’s needs are different in different situations. Depending on the situation, a peer may need to consider its trust in a specific aspect of another peer’s capability or in a combination of multiple aspects. Bayesian networks provide a flexible method to represent differentiated trust and combine different aspects of trust.

Decentralized peer-to-peer (P2P) networks can benefit from forming interest-based communities that can provide peers with information about the resources shared in the community and collectively computed rating of their quality as well as about the agents in the community and their reputation. We propose a mechanism for forming communities in a P2P system for sharing academic papers. The mechanism requires each agent to compute its trust in the agents with whom it interacts. A simulation shows that such communities can benefit peers.

It is important to enable peers to represent and update their trust in other peers in open networks for sharing files, and especially services. In this paper, we propose a Bayesian network-based trust model and a method for building reputation based on recommendations in peer-to-peer networks. Since trust is multifaceted, peers need to develop differentiated trust in different aspects of other peers' capability. The peer's needs are different in different situations. Depending on the situation, a peer may need to consider its trust in a specific aspect of another peer's capability or in multiple aspects. Bayesian networks provide a flexible method to present differentiated trust and combine different aspects of trust. The evaluation of the model using a simulation shows that the system where peers communicate their experiences (recommendations) outperforms the system where peers do not share recommendations with each other and that a differentiated trust adds to the performance in terms of percentage of successful interactions.

We propose a Bayesian network-based trust model. Since trust is multifaceted, even in the same context, agents still need to develop differentiated trust in different aspects of other agents' behaviors. The agent's needs are different in different situations. Depending on the situation, an agent may need to consider its trust in a specific aspect of another agent's capability or in a combination of multiple aspects. Bayesian networks provide a flexible method to present differentiated trust and combine different aspects of trust. A Bayesian network-based trust model is presented for a file sharing peer-to-peer application.