This chapter refers to the diversity and importance of recommendation systems based on the need for management of large quantities of data that is… [600541]
Recommendation Systems
Chirculescu Silviu Bogdan
University of Craiova
May 25, 2016
Abstract
This chapter refers to the diversity and importance of recommendation systems
based on the need for management of large quantities of data that is accumulated
from the users with the purpose of filtering the data after certain criteria. The
purpose for which recomandation systems were made represent a particular object
recommendation based on certain criteria and viewed from a certain point of view.
Recommendation systems are very useful in certain situations having the speed of
data filtering as the main advantage. These systems can be used in a variety of fields
from recommending web pages, articles, parks, restaurants, objects that can be sold as
cars , bicycles drinks, etc. At the same time these systems create a public profile based
on different characteristics of the objects in question.
I. Introduction
EE-commerce sites can have
large, essentially unbounded,
catalogs. With large catalogs
comes increasing difficulty for buy-
ers in making use of standard search
and browsing facilities. Particularly in
the case of casual or occasional buyers
and in the case of complex products,
the gap between a products specifica-
tions and the buyers understanding
of need can be hard to bridge. An ef-
fective e-commerce catalog must map
user needs to products that can ful-
fill them. This paper describes an in-
teractive, incremental, case-based, cri-
tiquing approach to solving this prob-
lem. The approach is interactive and
incremental, so it does not require
A thank you or further informationthat the user have a completely spec-
ified need at the start. The system is
case-based in that it emphasizes prod-
ucts over features or constraints, and
uses case-based reasoning techniques
for its product retrieval. Finally, the
approach is based on the critiquing
of presented examples, each critique
redirecting the search to home in on
appropriate products.
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