Angela Goh

An Entropy-Based Approach to Protecting Rating Systems from Unfair Testimonies

How to mitigate the influence of unfair testimonies remains an open issue in the research of rating systems. Methods have been proposed to filter the unfair testimonies in order to mitigate the influence of unfair testimonies. However, existing methods depend on assumptions that ratings follow a particular distribution to carry out the testimony filtering. This constrains them in specific rating systems and hinders their applications in other reputation systems. Moreover, existing methods do not scale well with the increase of testimony number due to their iterative nature. In this paper, a novel entropy-based method is proposed to measure the testimony quality, based on which unfair testimonies are further filtered. The proposed method does not require the assumption regarding the rating distribution. Moreover, it scales linearly with the increase of the testimony number. Experimental results show that the proposed method is effective in mitigating the influence of various types of unfair testimonies.

Improving collaborative filtering with trust-based metrics

Despite its success, similarity-based collaborative filtering suffers from some significant limitations, such as scalability and sparsity. This paper introduces trust to the domain of collaborative filtering to overcome these limitations. Compared with the similarity-based CF, introduction of trust does improve the performance of CF in terms of coverage, prediction accuracy, and robustness in the presence of attacks. Experimental results based on a real dataset are illustrated as evidences to support our claim.

Agent that models, reasons and makes decisions

We propose a computational agent-reasoning model (CAR) for constructing intelligent agent. Based on the CAR model, we present a new type of agent, computational intelligent agent (CIA), which has the ability to model, reason and make decisions on behalf of human beings. Unlike traditional intelligent agents, CIA is able to represent knowledge and carry out the inferences using numeric representations and computation instead of symbolic representation and deduction. Thus, the construction of CIA is simplified and the implementation code is compact. CIA also has the ability to handle various types of fuzzy information. It can be applied to various agent applications, especially for electronic commerce over the Internet. An example of CIA as a buying agent is illustrated.

A DYNAMIC INFERENCE MODEL FOR INTELLIGENT AGENTS

This paper proposes an Agent Inference Model (AIM) for constructing intelligent software agents. AIM has the ability of representing various types of fuzzy concepts, temporal concepts, and dynamic ...

Implementing ECA rules in an active database

Traditional database systems are designed to manage large volumes of data, but rule support is generally not a strong feature. On the other hand, expert systems have the deductive capability to manage rule processing. A coupling between these two systems to support advanced database applications results in what is termed an active database. An approach to implementing active database systems is to represent knowledge as Event–Condition–Action (ECA) rules. ECA rules determine when and how to react to different kinds of events. This paper focuses on the different type of events supported by an active database CLOSE. A set of primitive and composite events is presented together with examples of their application. Event detection in this system is also discussed.

Trust-based collaborative filtering

• In order to identify similar users, similarity-based collaborative filtering techniques usually go through the whole user profiles database to calculate the similarities between the active user and all the other existing users. All the computations are carried out by a central server. The computation burden of the server increases quickly with the increase of the size of the profile database, leading to poor scalability. • Users tend to rate few items, the user profile database is usually sparse. Due to the sparsity, it is quite often the case that users do not co-rate the minimum number of items in common required to compute the similarity. In many cases, it is only possible to select similar users from a small portion of all users [1].

Fuzzy cognitive maps for dynamic grid service negotiation

The grid is moving from the scientific grid to a pervasive and economic/business grid. Service trading, in which service provider and service consumer negotiate for a mutually acceptable agreement on multi-issues such as service performance, access cost etc., is one of the most important components in building the Economic Grid. In view of Pervasive Grid, a new challenging issue is that participants on pervasive devices usually have limited computational capacity. And it is also desirable that a multi-issue negotiation agreement can be reached as quickly as possible since the wireless communication to exchange the offers is generally unreliable and power-consuming. Hence, an agile, automated, but lightweight multi-issue decision-making model is needed to facilitate service negotiation in Pervasive Grid. More over, existing methods for multi-issue negotiation only regard each issue as a separate issue, though in most of cases, there exist causal relationships between these negotiation issues. In this paper, a decision-making model based on Fuzzy Cognitive Map (FCM) theory is proposed for multi-issue negotiation which takes into account the causal relationships between the negotiation issues. In the proposed model, the causal relationships between the negotiation issues are well represented by FCMs. The service trading is modeled as a dynamic system with interdependent relationships among negotiation issues. The example and experimental results show that the proposed model is lightweight and promising to be employed in Pervasive Grid for multi-issue service negotiations.

Dynamic negotiations for grid services

A market-oriented grid introduces an economic or market-oriented perspective to the grid. Negotiation is a vital component that facilitates the market-oriented grid. Negotiating agents play an indispensable role within the market-oriented grid. The extremely dynamic nature of grid makes agent negotiation a new challenging research issue. In this paper, a new agent negotiation model is proposed to support the dynamic agent-mediated negotiation in a market-oriented grid environment.

The Knowledge-Base of a B2B E-commerce Multi-agent System

Arising from economic globalisation, B2B e-commerce, which includes dynamic supply chain, business technology, and virtual organization, has grown considerably in the past few years. B2B E-Commerce is defined as commerce between businesses [1]. In order to stay competitive and to tap potential markets, it is necessary to enable consumers to customise their ever-changing demands. While most of the literature about software agents describes the use of agents to assist end users in B2C e-commerce, we propose the introduction of autonomous agents that can provide personalised information, undertake automated negotiations, and perform planning and scheduling functions [2,3,4] to support B2B e-commerce.

Managing consistency in collaborative design environments

In todays global economy, there is a significant paradigm shift to collaborative engineering design environments. One of key issues in the collaborative setting is the consistency model, which governs how to coordinate the activities of collaborators to ensure that they do not make inconsistent changes or updates to the shared objects. In this paper, we present a new consistency model which requires that all update operations will be executed in the casual order (causality) and all participants have the same view on the operations on the shared objects (view synchrony). A simple multicast-based protocol to implement the consistency model is presented. By employing vector time and token mechanisms, the protocol brings the shared objects from one consistent state to another, thus providing collaborators with a consistent view of the shared objects. A CORBA-based on-going prototyping implementation is outlined. Some of the related work are also discussed.