basis of adaptation by adding models of context such as location, time, computing
platform and bandwidth to the classic user model and exploring the use of known
adaptation technologies to adapt to both an individual user and a context of their work.
Now, customer needs imply both, the thematic preferences (i.e., the traditional notion of
profile) the device profile (i.e., the characteristics of the mobile device),.To this end,
adaptive personalization is concerned with the negotiation of customer requirements and
device abilities.
Indisputably, the user population is not homogeneous, nor should be treated as such.
To be able to deliver quality services, eBusiness Services should be tailored to the needs
of individual customers providing them with personalized and adaptive information upon
request. Although one-to-one service provision may be a functionality of the distant
future, customer segmentation is a very valuable step towards that direction. Customer
segmentation means that the customers are subdivided (ideally per service or group of
related services, based on their demographic characteristics, socio-economic
characteristics, psychographic characteristics, or individual physical and psychological
characteristics), into more or less homogeneous, mutually exclusive subsets of customers
who share an interest in the service.
The issue of personalization is rather complex. And it becomes even more
complicated once viewed from a moving user’s perspective. The new issues now also
include: what content to present to the user, how to show the content to the user, how to
ensure the user’s privacy, or how to create a global personalization scheme [7]. In
addition, there are also many approaches each of which focuses on a specific area, i.e.
whether this is profile creation, machine learning and pattern matching, data and web
mining or personalized navigation. Personalization varies from Link to Content to Context
to Authorized to Humanized levels, with several paradigms to implement them. Among
others these include, content-based filtering, rule-based filtering, collaborative filtering,
Web-usage mining, demographic-based filtering agent technologies, and cluster models.
Having these in mind Business Analysts and Practitioners should develop new intelligent
user interfaces advanced with adaptive presentation and adaptive navigation techniques
that would take advantage of these constraints to the benefits of their customers whenever
applicable and provide them with uninterrupted sustainable eServices.
6 Conclusion
The rapid expansion of the adoption of the Internet as a communication medium, as well
as the explosive growth in the size and use of the World Wide Web and the need for
eBusiness Services to retain their customers and therefore gain a substantial competitive
advantage results in the inference that Web Personalization techniques, like intelligent
user interfaces, enable eBusiness services providers to adopt successfully the new multi-
channel (wireless and mobile) technologies increasing their eServices provision
sustainability across their market segments. This paper analyzed key concerns about
customers’ requirements for multi-channel service provision anywhere, anytime and
anyhow, thus re-enforcing core functionality issues related to mobility, and therefore
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