英语翻译下面是一篇英文,帮我看一下是啥呢么意思,不需要逐字逐句翻译说清意思即可Project:Implement and

英语翻译
下面是一篇英文,帮我看一下是啥呢么意思,不需要逐字逐句翻译说清意思即可
Project:Implement and Test Item-Based Collaborative Filtering
Recommendation Algorithmsi
The amount of information in the world is increasing far more quickly than our ability to
process it.All of us have known the feeling of being overwhelmed by the number of new books,
movies,and journal articles coming out each year.Technology has dramatically reduced the
barriers to publishing and distributing information.Now it is time to create the technologies
that can help us sift through all the available information to find that which is most valuable to
us.One of the most promising such technologies is collaborative filtering,which has been
very successful in both research and practice,and in both information filtering applications and
E-commerce applications.
The Question
The goal of a collaborative filtering algorithm is to suggest new items or to predict the utility of
a certain item for a particular user based on the user's previous likings and the opinions of other
like-minded users.In a typical CF scenario,there is a list of m users { ,,,} 1 2 m U  u u  u and a
list of n items { ,,,} 1 2 n   i i  i .Each user ui has a list of items Iui,which the user has expressed
his/her opinions about.Opinions can be explicitly given by the user as a rating score,generally
within a certain numerical scale,or can be implicitly derived from purchase records,by
analyzing timing logs,by mining web hyperlinks and so on.Note that I ui   and it is possible
for Iui to be a null-set.There exists a distinguished user U U a  called the active user for whom
the task of a collaborative filtering algorithm is to find an item likeliness that can be of two
forms.
 Prediction is a numerical value,Pa,j,expressing the predicted likeliness of item
j ua i I for the active user ua.This predicted value is within the same scale (e.g.,from 1
to 5) as the opinion values provided by ua.
 Recommendation is a list of N items,I r   ,that the active user will like the most.
Note that the recommended list must be on items not already purchased by the active
user,i.e.,    r ua I .This interface of CF algorithms is also known as Top-N
recommendation.
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