Relationship of accurate associations between non-coding RNAs and diseases could be of
great help in the treatment of human biomedical research. However, the traditional …

Detecting potential associations between drugs and diseases plays an indispensable role in
drug development, which has also become a research hotspot in recent years. Compared …

Link prediction tasks focus on predicting possible future connections. Most existing
researches measure the likelihood of links by different similarity scores on node pairs and …

Predicting associations in drug–disease network provides effective information for the drug
repositioning. Therefore, it is an important task to develop an effective drug–disease …

Identification of associations between non-coding RNAs and diseases plays an important
role in the study of pathogenesis, which has been a hot topic in recent research. However …

There are an increasing number of manufacturing service resources appeared on the cloud
manufacturing (CMfg) service platform recently, which leads to a serious information …

We propose a new method for bipartite link prediction using matrix factorization with
negative sample selection. Bipartite link prediction is a problem that aims to predict the …

With the popularity of social media, including micro-blog, mining effective information in
short texts has become an increasingly important issue. However, due to the sparseness …

A bipartite network is a special type of network structure that possesses unique value and
practical significance in numerous fields, including recommender systems, social networks …

Link prediction in bipartite networks aims to identify or predict possible links between nodes
of different types based on known network information. However, most existing studies …