Information Technology Reference
In-Depth Information
Chapter 5
Semantic Movie Recommendations
Andreas Lommatzsch
Abstract
The overwhelming amount of video and audio content makes it difficult
for users to find new high-quality content matching the individual preferences. Rec-
ommender systems are built to suggest potentially interesting items by computing the
similarity between users and items. The big challenges while creating recommender
systems are the sparsity of data (the knowledge about users and items is often limited)
and the popularity bias (most recommender algorithms tend to recommend popular
items already known to the user). Semantic techniques supporting the graph-based
representation of knowledge and the integration of heterogeneous datasets allow us
to overcome these problems. The aggregation of knowledge from several different
sources enables us to take into account many different aspects while computing
recommendations. In addition, semantic recommender systems can provide expla-
nations for suggested items helping the user to understand why an unknown item
matches the individual user preferences. In this chapter we discuss the challenges in
creating recommender systems and explain semantic approaches for the recommen-
dation domain. We discuss the steps for building a semantic recommender system
and present a semantic movie recommender system in detail. The advantages of
semantic recommender systems compared to traditional recommender approaches
are analyzed.
Having a Wonderful Video Evening
It is a cold and dark December late afternoon. Carl, Clara, and Steven have enjoyed
thewonderful winter weather having several snowball fights with some school friends
in the park. But now a strong wind comes up and Carl, Clara, and Steven return home
hungry. In the comfortable well-heated living room they sit around the old round oak
table. Suzanne serves hot chocolate for the kids and ginger tea with lemon and honey
for Steven. On the table, there are fresh cookies made based on the secret recipe she
learned from her great-grandmother. Since outside the whether become very windy,
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