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62 PERSONALIZATION ANDCUSTOMIZATIONTECHNOLOGIESparticipating companies, such as Citigroup, General Mo-
tors Corporation, and Sony Corporation, which together
form the Liberty Alliance Network. Liberty Alliance also
allows users to decide whether to link their accounts to dif-
ferent participating sites. For example, users can choose
to opt out and not link their accounts to a specific site. The
main difference between Microsoft Passport and Liberty
Alliance is that Microsoft keeps all the data about individ-
ual users, whereas Liberty Alliance allows the data to be
owned by many Web sites.CONCLUSION
Personalization and customization are among the fastest
growing segments of the Internet economy. They pro-
vide several advantages to both businesses and customers.
Customers benefit from personalization by receiving cus-
tomized experience, reduced information overload, and
personalized products and services. Businesses benefit
from the ability to learn consumers’ behavior, provide
one-to-one marketing, increase costumer retention, op-
timize product selection, and provide build-on-demand
services.
Due to the large variety of personalization techniques
and applications, this survey is by no means exhaustive.
Recent developments in Web services, for example, of-
fer new prospects for personalization and customization.
SUN recently presented a new vision of context-sensitive
Smart Web services, which can adapt their behavior
to changing conditions. A smart Web service can adapt
depending on a user’s location or preferences.
Personalization is by no means limited to Web site data
mining, machine learning, or statistical analysis. Person-
alization can use any technology that provides insight
into customer behavior and customer preferences. It is
our hope and expectation that the near future will of-
fer new challenging technologies and that personalization
will continue to be one of the most exciting fields in the
modern Internet economy.GLOSSARY
Anonymizer A proxy between a browser and a Web site
which hides the user’s identity.
Collaborative filtering Recommendation technology
that makes a suggestion to a target customer by finding
a set of customers with similar interests.
Content-based recommendation Recommendation
technology that makes a suggestion to a target cus-
tomer by finding items similar to those he or she has
liked or has purchased in the past.
Cookie The data sent by a Web server to a Web client,
stored locally by the client and sent back to the server
on subsequent requests.
Customer profile A collection of data describing an in-
dividual user or a group of users.
Data mining The nontrivial process of identifying valid,
novel, potentially useful, and ultimately understand-
able patterns in data.
Intelligent agent A software program which can act as
a proxy of a human user by learning and reasoning
about users’ preferences.Log file A file generated by a Web server, which keeps a
record for every transaction.
Personalization Using user information to better de-
sign products and services tailored to the user.
Privacy The claim of individuals, groups, or institutions
to determine for themselves when, how, and to what
extent information about them is communicated to
others.
User identification The process of associating Web site
visits and navigation behavior with a particular user.
User session All activities performed by a user during a
single visit to a Web site.
Web bug A hidden image in a Web page that activates a
third-party spying device without being noticed by the
Web page visitors.CROSS REFERENCES
SeeData Mining in E-commerce; Intelligent Agents; Ma-
chine Learning and Data Mining on the Web; Rule-Based
and Expert Systems.REFERENCES
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