Search Results for "natural language processing"

The node2vec project provides an implementation of the node2vec algorithm, a scalable feature learning method for networks. The algorithm is designed to learn continuous vector representations of nodes in a graph by simulating biased random walks and applying skip-gram models from natural language processing. These embeddings capture community structure as well as structural equivalence, enabling machine learning on graphs for tasks such as classification, clustering, and link prediction. The repository contains reference code accompanying the research paper node2vec: Scalable Feature Learning for Networks (KDD 2016). ...

This domain specific language lets you declare complex java objects with a Json-like notation. In addition to that, it lets you specify in a natural way what the mockito mocks should return when called with a given value.