Staring at a shelf full of Photoshop books at the local bookstore, it seems that there are more special-effect “cookbooks” and technical tomes than anyone would ever care to read. The problem is that none of those “cookbooks” provide enough detail to really let you feel like you understand the program (blindly following the listed steps just doesn’t do it), and all of the technical books are deep into terms like rasters, vectors, and bit-depth settings. That’s the primary reason that most people
The vast amount of information available on the Internet, coupled with the diversity
of user information needs, have urged the development of personalized systems that
are capable of distinguishing one user from the other in order to provide content, services
and information tailored to individual users. Recommender Systems (RS) form
a special category of such personalized systems and aim to predict user’s preferences
based on her previous behavior. Recommender systems emerged in the mid-90’s and
since they have been used and tested with great success in e-commerce, thus offering
a powerful tool to businesses activating in this field by adding extra value to their
customers. They have experienced a great success and still continue to efficiently
apply on numerous domains such as books, movies, TV program guides, music,
news articles and so forth.
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