Given a graph G where each node is associated with a set of attributes, attributed network
embedding (ANE) maps each node v∈ G to a compact vector Xv, which can be used in …

Sentiment analysis of the text deals with the mining of the opinions of people from their
written communication. With the increasing usage of online social media platforms for user …

Identifying influential nodes in complex networks through influence diffusion models is a
challenging problem that has garnered significant attention in recent years. While many …

In the era of big data, the large-scale information network applications need to process and
analyze increasingly complex graph structure relationships. However, traditional methods of …

Network representation learning (NRL) is a powerful technique for learning low-dimensional
vector representation of high-dimensional and sparse graphs. Most studies explore the …

Given a graph G where each node is associated with a set of attributes, attributed network
embedding (ANE) maps each node v∈ G to a compact vector X v, which can be used in …

Graphs are ubiquitous today and are a fundamental data structure to represent objects and
their relations in various domains, eg, social science, citation analysis, weblink analysis, and …

With the advent of big data, graphs have gained popularity as one of the most efficient data
storage mechanisms. A graph can not only capture relationships between entities, but it can …