Department of Computer and Information Science

Online trading environments such as business-to-business (B2B) e-commerce enable companies to tender projects and/or to procure goods with low costs and rapid responses. Agent-based architectures are an effective platform for such purposes because they provide mechanisms to allow companies to advertise their deals, exchange information, and perhaps to bargain over the deals before they can be closed in some kind of automated fashion. This is a classical problem of doing automated agent negotiation in which the process could be complex. In this paper, we examine the possibilities of applying an object-oriented ontology called Knowledge Beads (KB) for enabling agent negotiation and representing the knowledge collected over the negotiation process. We propose a KB-supported agent architecture and discuss its features for supporting B2B trading. In particular, we focus upon KB's use of inheritance capability as a knowledge representation medium, and show how it contributes to the fusion of proposal formation, negotiation actions and knowledge management.

Collaborative writing through wikis has become increasingly popular in recent years. When users contribute to a wiki article they implicitly establish a co-authorship relationship. Discovering these relationships can be of value, for example in finding experts on a given topic. However, it is not trivial to determine the main co-authors for a given author among the potentially thousands who have contributed to a given author's edit history. We have developed a method and algorithm for calculating a co-authorship degree for a given pair of authors. We have implemented this method as an extension for the MediaWiki system and demonstrate its performance which is satisfactory in the majority of cases. This paper also presents a method of determining an expertise group for a chosen topic.

A double agents-based model in a make-to-order supply chain (MTOSC), called Collaborative Single Machine Earliest/Tardiness model (CSET model) is proposed. It integrates Pareto-optimal method with Just-in-Time principle (JIT) into two intelligent agents for optimizing dynamic supply-chain formation and scheduling respectively. This model mainly focuses on improving the sequence timing factor. JIT is able to shorten the waiting time while Pareto-optimality provides a mechanism that each participant won't suffer loss. Combining the two methods, an unprecedented efficiency on supply chain (SC) can be achieved. We have compared how our proposed method performed in various MTOSC formations. The experimental results indicate that CSET model yields time improvement on the SC workflows.

Most of the electronic commerce businesses have to address the same issues such as the four core business activities namely Attract, Interact, Act and React. The success of an E-Commerce business hinges on how competent the personnel who operate the four activities are. In this paper, we identify the job functions of the personnel for a typical Internet retail. In particular, we present an object-oriented model of the personnel specialized for Internet-based retail business. The model is designed according to the four core business activities. The personnel are designed to support the fundamental functions that make a successful E-Commerce business. Our model can serve as a high-level infrastructure planning or ERP for Internet retail, and it can be modified to suit other E-commerce domains such as Business-to-Business commerce.

Supply chains have evolved to web-applications that tap on the power of internet to expand their networks online. Recently some research attention is focused on make-to-order supply chain formation where orders are scheduled to be optimally distributed among online manufacturers and suppliers for mutual benefits. A SET model was proposed in [1] using Pareto theories. The model is then extended into a collaborative manner throughout the whole supply chain by incorporating it with the Just-in-Time (JIT) principle, known as CSET. The CSET framework was proposed, and the advantage of time efficiency was shown in . The core of the CSET model is based on intelligent agent technology. Specifically the model is supported by double-agent architecture with each type of agents who makes provisional plans of order distribution by Pareto optimality and JIT coordination respectively. This paper defines such double-agent mechanisms in details, as well as demonstrating its merits via simulation study.

This paper presents a knowledge empowered automated negotiation system for buyer-centric multi-bilateral multi-attribute e-Procurement. We propose two knowledge empowered models namely KERM and KACM. KERM is used for the buyer to determine a list of suppliers which are the best qualified candidates to negotiate with. KERM also allows the flexibility to assign appropriate weights, based on buyer's interests, to each knowledge factor affecting the overall evaluation result of a quote. The resulted list of quotes of high rank is believed to produce satisfactory negotiation result for the buyer. KACM enables an automated concession process, while at the same time facilitates a flexible negotiation via the use of concept switch and tagged rules. KACM emphasizes the utilization of knowledge originated from the historical negotiation data in estimating and fine-tuning the negotiation parameters for improving the performance of automated negotiation. Our results show that the prototype makes significant improvement in the satisfaction level of negotiation results.

In an effort to compose an optimal supply chain (SC), this paper tries to bring forward a new collaborative agent-based single machine earliness/tardiness (SET) model. It includes the sub-agents, which are designed for fairly coordinating and distributing job requests at the mid-stream levels. Extending from the precedent SET model, collaborative-SET (CSET) has a coordinating collaborative agent, which is responsible for optimising the information flow and scheduling of the whole SC. This is done by coordinating the information flow at the sub-agent between each two streams. In a long run, this new model makes a complex dynamic SC more efficient and shortens response time. A stimulator that implements the algorithms is programmed in order to calculate the amount of information transfer, time and cost incurred between SET and CSET model. The results generally indicate that the more streams a SC has, the better the performance gain is yielded.

Recent studies show that the number of mobile devices has already exceeded the number of personal computers. Contradictorily, the commerce conducted via the mobile devices ("M-Commerce") is far less than that of internet ("E-Commerce"). This paper looks into the context of the mobile commerce from two dimensions. (i) The framework of mobile payment system, the mobile payment model, the classification of mobile payment and mobile service. Spinning out from these discussions, it helps to provide a better understanding of how the mobile payment model is constructed and what m-commerce is all about. (ii) From the user's perspective, the user acceptance analysis of the mobile users and the mobile commerce system, in which the characteristic of the users, the constraints of the system are discussed. With these two dimensions in mind, the application scenarios of the m-commerce system, that is, the situations where mcommerce can put forth to perform required task, are suggested. Our empirical results show that although people in Macau think using mobile phone is an innovative and convenient tool for making payment, the acceptance level is still not very high.

Steam data are continuous and ubiquitous in nature which can be found in many Web applications operating on Internet. Some instances of stream data are web logs, online users' click-streams, online media streaming and Web transaction records. Stream Mining was proposed as a relatively new data analytic solution for handling such streams. It has been widely acclaimed of its usefulness in real-time decision-support applications, for example web recommenders. Hoeffding Tree Algorithm (HTA) is one of the popular choices for implementing Very-Fast-Decision-Tree in stream mining. The theoretical aspects have been studied extensively by researchers. However, the data streams that fed into HTA are usually assumed at a constant rate in the literature. HTA has yet been tested under bursty traffic such as Internet environment. This paper sheds some light into the impact of bursty traffic on the performance of HTA in stream mining.

Business Intelligence (BI) capitalized on datamining and analytics techniques for discovering trends and reacting to events with quick decisions. We argued that a new breed of data-mining, namely stream-mining where continuous data streams arrive into the system and get mined very quickly, stimulates the design of a new real-time BI architecture. In the past, stream-mining (especially in algorithmic level) and digital information system architectures have been studied separately. We attempted in this paper to present a unified view on the real-time BI system architecture powered by stream-mining. Some typical applications in which our architecture can support are described.

Security in physical environments has become increasingly important in the wake of terror and criminal activity, particularly over the past decade. One of the challenges is to identify activities that may not be outright illegal or breaches of security, but that are suspicious, i.e. where there is a possibility that these activities may lead to breaches of security. Technology such as RFID is used to track the access and movement of people in highly security physical environments. This paper presents methods of detecting patterns of suspicious activity in logs collected by such physical access control systems. It also outlines methods of predicting future suspicious activities based on such logs.

This paper discusses about how business intelligence on a website could be obtained from users' access records instead of web logs of "hits". Users' access records are captured by implementing an Access-Control (AC) architectural model on the website. This model requires users to register their profiles in an exchange of a password; and thereafter they have to login before gaining access to certain resources on the website. The links to the resources on the website have been modified such that a record of information about the access would be recorded in the database when clicked. This way, datamining can be performed on a relatively clean set of access records about the users. Hence, a good deal of business intelligence about the users' behaviors, preferences and about the popularities of the resources (products) on the website can be gained. In this paper, we also discussed how the business intelligence acquired, in turn, can be used to provide e-CRM for the users.

Wikis, best represented by the popular and highly successful Wikipedia system, have established themselves as important components of a collaboration infrastructure. We suggest that the complex network of user-contributors in volunteercontributed wikis constitutes a digital ecosystem that bears all the characteristics typical of such systems. This paper presents an analysis supporting this notion based on significance of authorship within the wiki. Our findings confirm the hypothesis that large volunteer-contributed wikis are digital ecosystems, and thus that the findings from the digital ecosystems research stream are applicable to this type of system.

Shared-buffer switches have many advantages such as relatively low cell loss rate and good buffer utilization, and they are increasingly favoured in recent VLSI switch designs for ATM. However, their performance degrades dramatically under nonuniform traffic due to the monopolization of the buffer by some favoured cells. To overcome this, restricted types of sharing and hot-spot pushout (HSPO) have been proposed, and the latter has been shown by simulation to perform better in all situations. In this paper we develop an analytical model for performance evaluation of a shared-buffer asynchronous transfer mode (ATM) switch with HSPO under bursty traffic. This analytical model is an improved version of the first model ever developed for this purpose. We balance the relative queues to approximate the effects of pushout, while keeping only four state-variables, and our model gives a good agreement with simulation, for calculating throughput and cell loss. ᭧

The emerging technology in mobile devices presents new business potential to Internet enterprises. These devices enable users to access the Internet at any time in any location. Based on the infrastructure of the existing e-commerce applications, these enterprises can extend their services to the vast population of mobile users by redesigning some of their business process. Taking the E-Ticket system as an example, this paper examines the requirements of m-commerce applications, and explores the benefits that mobility contributes by investigating how the electronic ticketing service can be extended to the mobile users.