Abstract:
The World Wide Web information grows
explosively in the Internet and people encounter
problem to pick some correct things from the
overwhelming set of choices. The recommender
systems help them choose something they actually
want or need. Many of the E-commerce Web sites
are already using recommender systems to
facilitate their buyingprocess. Collecting taste
information from many users is important to
recommend relevant items to the user. The system
intends to recommend most relevant items in the
online electronic devices shopping system. In this
system Item-to-Item collaborative filtering method
makes recommendations about the interest of a
user based on history data. Cosine similarity is
used to compute the similarity between two item
pairs.
