Recommender systems have been widely adopted in online applications to suggest
products, services, and contents to potential users. Collaborative filtering (CF) is a …

Collaborative filtering is an emerging technology to deal with information overload problem
guiding customers by offering recommendations on products of possible interest. Forming …

We present a mixture model based approach for learning individualized behavior models for
the Web users. We investigate the use of maximum entropy and Markov mixture models for …

User profiles can be used to identify persons inside a community with similar interests.
Folksonomy systems allow users to individually tag the objects of a common set (eg, web …

Web users display their preferences implicitly by navigating through a sequence of pages or
by providing numeric ratings to some items. Web usage mining techniques are used to …

From e-commerce to e-learning, recommendation systems have given birth to an important
and thriving research niche and have been deployed in a variety of application areas over …

—Customer product reviews play an important role in the customer's decision to purchase a
product or use a service. Customer preferences and opinions are affected by other …

In this tutorial, we present an overview of the personalization field and review different types
of personalization. We also discuss the general personalization process and position the …

When speaking of information retrieval, we often mean text retrieval. But there exist many
other forms of information retrieval applications. A typical example is collaborative filtering …

The importance of accurate recommender systems has been widely recognized by
academia and industry, and recommendation is rapidly becoming one of the most …