Abstract:
Information filtering systems, which
recommend appropriate information to users from
enormous amount of information, are becoming
popular. Recommender systems are programs
which attempt to predict items that a user may be
interest in and depends on information provided
by the users to gather knowledge. Content –based
filtering systems are based on profile attributes. In
content-based filtering, items are matched either
to a user’s interest profile or query on the basis of
content. Content-based system does not use any
preference data and provides recommendation
directly based on similarity of items.Contentbased
recommendation systems may be used in a
variety of domains ranging from recommending
web pages, news articles, restaurants, television
programs, and items for sale. This system is an
implementation of recommender system for movies
using content-based filtering method.Rated movies
from IMDb are used in this system. And the users
must register and fill the profile to get
recommendation because it calculates
recommendation score depend on the user profile.
This system recommends movies with
recommendation score to the user finally and is
implemented by using Microsoft SQL server and
C# programming.
