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Books > Computing & IT > Computer communications & networking > Network security
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Towards Sustainable Society on Ubiquitous Networks - The 8th IFIP Conference on e-Business, e-Services, and e-Society (I3E 2008), September 24 - 26, 2008, Tokyo, Japan (Paperback, Softcover reprint of hardcover 1st ed. 2008)
Loot Price: R3,050
Discovery Miles 30 500
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Towards Sustainable Society on Ubiquitous Networks - The 8th IFIP Conference on e-Business, e-Services, and e-Society (I3E 2008), September 24 - 26, 2008, Tokyo, Japan (Paperback, Softcover reprint of hardcover 1st ed. 2008)
Series: IFIP Advances in Information and Communication Technology, 286
Expected to ship within 10 - 15 working days
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The massive growth of the Internet has made an enormous amount of
infor- tion available to us. However, it is becoming very difficult
for users to acquire an - plicable one. Therefore, some techniques
such as information filtering have been - troduced to address this
issue. Recommender systems filter information that is useful to a
user from a large amount of information. Many e-commerce sites use
rec- mender systems to filter specific information that users want
out of an overload of - formation [2]. For example, Amazon. com is
a good example of the success of - commender systems [1]. Over the
past several years, a considerable amount of research has been
conducted on recommendation systems. In general, the usefulness of
the recommendation is measured based on its accuracy [3]. Although
a high - commendation accuracy can indicate a user's favorite
items, there is a fault in that - ly similar items will be
recommended. Several studies have reported that users might not be
satisfied with a recommendation even though it exhibits high
recommendation accuracy [4]. For this reason, we consider that a
recommendation having only accuracy is - satisfactory. The
serendipity of a recommendation is an important element when c-
sidering a user's long-term profits. A recommendation that brings
serendipity to users would solve the problem of "user weariness"
and would lead to exploitation of users' tastes. The viewpoint of
the diversity of the recommendation as well as its accuracy should
be required for future recommender systems.
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