Interactive calligraphy experience equipment has the characteristics of a large amount of
data, various types, and strong homogeneity, which makes it difficult for users to find …

Using trust relationships can improve the accuracy of recommendation systems; however, it
is affected by data sparsity. Random walks can harvest the behavioral relationships between …

Recommender systems (RS) are increasingly leveraging the power of graphs to enhance
accuracy. However, we stipulate that existing methods don't take into consideration the …

In this paper we present a graph-based recommender system that is not relying on explicit
item ratings to generate recommendations. Instead, it employs neighborhood-based and …

A personalized recommendation system learns users specific profiles from users feedback
and content in order to deliver information tailored to each individual user's interest …

Drug discovery focuses on understanding different types of interactions from drug-drug
interactions (DDIs) to drug-food interactions (DFIs). The main purpose of DFI is to discover …

Community detection and recommender systems are two subjects of the highest relevance
among data-oriented computational methods, considering their current applications in …

Recommender Systems (RS) are software tools which can be used in making useful
predictions of items to users. RS has been an important research area since the mid-1990s …