The emergence of new TV media such as digital cable and satellite has diversified TV
contents. This makes the task of finding one's favorite contents among hundreds of TV …

In this paper, we present an intelligent information filtering strategy that is a hybrid of item-
based Collaborative Filtering (CF) and Case Based Reasoning (CBR) methods. Information …

Recommendation systems are being explored by Cable TV operators to improve user
satisfaction with services, such as Live TV and Video on Demand (VOD) services. More …

(SVD) to let the system better understand the semantics of the pedagogical resources in a
content-based approach and prevent some shortcomings of the existing collaborative …

Product recommendation is very important in business to customer (B2C) e-commerce.
Automated Collaborative Filtering (ACF) is an important approach for product …

Academic collaboration can be grouped by different faculty members. It involves searching
for relevant research topics to collect and analyze information and establishing a new …

In the current big data era, recommendation systems play an important role in our daily life to
help us make faster and better decisions from massive amounts of choices. However, the …

With the rising integration of more and more online data sets with various hardware
platforms, such as set-top boxes, mobile phones, it becomes increasingly crucial to have …

Since the introduction of Web 2.0, group recommendation systems become an effective tool
for consulting and recommending items according to the choices of group of likeminded …

There are two main techniques used to capture an individual's personal preferences in order
to make recommendations to them about various items of interest: feature-based and clique …