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Customised Electronic Commerce with Intelligent Software Agents
Abstract
This chapter describes a conceptual framework for designing and developing software agents that will enable customized electronic commerce (CEC) and highlights several important constructs as well as their interrelationships within the framework. In particular, it examines the enabling technologies under two categories, namely, on-line cataloging and recommendation. In order to demonstrate some of the key characteristics of customized electronic commerce, this chapter also presents three prototyped software agents, namely, ETA (Electronic Tour Agent), EPA (Electronic Property Agent), and EAA (Electronic Auction Agent).
The advance of Internet and Web technologies has boosted the development of electronic commerce. More and more people have changed their traditional trading behaviors and started to conduct Internet shopping. However, the exponentially increasing product information provided by Internet enterprises causes the problem of information overload, and this inevitably reduces the customer's satisfaction and loyalty. To overcome this problem, in this paper we propose a multi-agent system that is capable of eliciting expert knowledge and of recommending optimal products for individual consumers. The recommendations are based on both product knowledge from domain experts and the customer's preferences from system–consumer interactions. In addition, the system also uses behavior patterns collected from previous consumers to predict what the current consumer may expect. Experiments have been conducted and the results show that our system can give sensible recommendations, and it is able to adapt to the most up-to-date preferences for the customers.
This paper is about a new research field called Web Intelligence (WI for short). We try to explain the needs for coining the term as a sub-discipline of computer science for systematic studies
on advanced Web related theories and technologies, as well as the design and implementation of Intelligent Web Information
Systems (IWIS). Background information and related topics are discussed in an attempt to demonstrate why we consider WI to
be a subject worthy of study and, at the same time, to establish a starting point for the further development of WI.
Travel Comparison Websites (TCWs) use intelligent agent technology to help their users sort the information available for a particular travel related query and make comparisons between the alternatives available before making a booking decision. Given the fact that comparison- shopping sites have grown in popularity over the past year, TCWs may become another interesting online travel distribution channel. The present study first presents a taxonomy of TCWs and using a web-experiment with 149 participants in UK and in Greece assesses the factors that influence user perception of the various types of sites and the propensity of returning to them for future travel information-seeking tasks. The study showed that users prefer well-established online brands and that price comparison is not their only concern. Portal-associated TCWs came second in user preference while the newcomers have still a lot to do in order to survive. The findings of the study may be used by various travel suppliers when considering their affiliation to particular TCWs.
Ant routing is a method for network routing in agent technology. Although its effectiveness and efficiency have been demonstrated and reported in the literature, its properties have not yet been well studied. This paper presents some preliminary analysis on an ant algorithm in regard to its population growing property and jumping behavior. Results conclude that as long as the value max, {iΩj|} is known, the practitioner is able to design the algorithm parameters, such as the number of agents being created for each request, k, and the maximum allowable number of jumps of an agent, in order to meet the network constraint.
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