A filter bubble refers to the phenomenon where Internet customization effectively isolates
individuals from diverse opinions or materials, resulting in their exposure to only a select set …

While personalization increases the utility of recommender systems, it also brings the issue
of filter bubbles. eg, if the system keeps exposing and recommending the items that the user …

Recommender systems usually face the issue of filter bubbles: over-recommending
homogeneous items based on user features and historical interactions. Filter bubbles will …

Due to underlying privacy-sensitive information in user-item interaction data, the risk of
privacy leakage exists in the centralized-training recommender system (RecSys). To this …

With the development of Augmented Reality (AR) technology in the retail industry, virtual
fitting room (VFR) are considered promising enhancement of e-commerce by providing …

Recommender Systems (RSs) typically face the cold-start problem and the filter-bubble
problem when users suffer the familiar, repeated, and even predictable recommendations …

Social networks are a platform for individuals and organizations to connect with each other
and inform, advertise, spread ideas, and ultimately influence opinions. These platforms have …

Friend recommendation service plays an important role in shaping and facilitating the
growth of online social networks. Graph embedding models, which can learn low …

Workplace communication software such as Microsoft Teams, Slack, and Google Workspace
have become integral to workplace collaboration, especially due to the rise of remote work …

While social networks greatly facilitate information dissemination, they are well known to
have contributed to the phenomena of filter bubbles and echo chambers. This in turn can …