node2vec (Grover and Leskovec, 2016) is a machine learning method used to create vector representations of the nodes of a graph. More information about node2vec can be found here. This repository ...

Learning low-dimensional representations (embeddings) of nodes in large graphs is key to applying machine learning on massive biological networks. Node2vec is the most widely used method for node ...

It could happen that the gensim recently changed the default values (https://radimrehurek.com/gensim/models/word2vec.html#gensim.models.word2vec.Word2Vec) though, as ...

Random walks have been proven to be useful for constructing various algorithms to gain information on networks. Algorithm node2vec employs biased random walks to realize embeddings of nodes into ...

Prediction tasks over nodes and edges in networks require careful effort in engineering features used by learning algorithms. Recent research in the broader field of representation learning has led to ...

Abstract: In this study, we conducted a comparative evaluation of two popular embedding techniques, Word2Vec and Node2Vec, to enhance recommendation systems for frequently bought together products in ...

Abstract: Many biological studies show that microRNAs (miRNAs) play an indispensable role in the regulation of various biological processes. MiRNAs are significant biomakers in disease diagnosis, ...