A new link prediction in multiplex networks using topologically biased random walks
Link prediction is a technique to forecast future new or missing relationships between nodes
based on the current network information. However, the link prediction in monoplex …
based on the current network information. However, the link prediction in monoplex …
Enhanced ensemble clustering via fast propagation of cluster-wise similarities
Ensemble clustering has been a popular research topic in data mining and machine
learning. Despite its significant progress in recent years, there are still two challenging …
learning. Despite its significant progress in recent years, there are still two challenging …
Robust ensemble clustering using probability trajectories
Although many successful ensemble clustering approaches have been developed in recent
years, there are still two limitations to most of the existing approaches. First, they mostly …
years, there are still two limitations to most of the existing approaches. First, they mostly …
'NetShift': a methodology for understanding 'driver microbes' from healthy and disease microbiome datasets
BK Kuntal, P Chandrakar, S Sadhu… - The ISME journal, 2019 - academic.oup.com
The combined effect of mutual association within the co-inhabiting microbes in human body
is known to play a major role in determining health status of individuals. The differential …
is known to play a major role in determining health status of individuals. The differential …
Hybrid approach for detecting propagandistic community and core node on social networks
People share their views and daily life experiences on social networks and form a network
structure. The information shared on social networks can be unreliable, and detecting such …
structure. The information shared on social networks can be unreliable, and detecting such …
Multi-level learning based memetic algorithm for community detection
Complex network has become an important way to analyze the massive disordered
information of complex systems, and its community structure property is indispensable to …
information of complex systems, and its community structure property is indispensable to …
Application of natural computation inspired method in community detection
The study of community structure in complex networks has always been a subject of great
concern in various fields. Community structure can reflect the dynamic characteristics and …
concern in various fields. Community structure can reflect the dynamic characteristics and …
Identifying breast cancer-related genes based on a novel computational framework involving KEGG pathways and PPI network modularity
Complex diseases, such as breast cancer, are often caused by mutations of multiple
functional genes. Identifying disease-related genes is a critical and challenging task for …
functional genes. Identifying disease-related genes is a critical and challenging task for …
Personalized pagerank clustering: A graph clustering algorithm based on random walks
Graph clustering has been an essential part in many methods and thus its accuracy has a
significant effect on many applications. In addition, exponential growth of real-world graphs …
significant effect on many applications. In addition, exponential growth of real-world graphs …
Higher order connection enhanced community detection in adversarial multiview networks
Community detection in multiview networks has drawn an increasing amount of attention in
recent years. Many approaches have been developed from different perspectives. Despite …
recent years. Many approaches have been developed from different perspectives. Despite …