项目作者： tanishkasingh9
项目描述 ：
Aim is to convert nodes and node attributes of the DBLP Citation graph to analyze graph specific trends. This objective entailed two tasks, recreating a search algorithm for sampling the neighborhood as per the Node2Vec algorithm and extract feature embeddings using the Word2Vec skip-gram architecture. The nodes (papers)are represented into a fixed size multi-space dimension that is capable of capturing closeness of two papers based on a mentioned metric. The final classification of groups is based on the feature embeddings, performed by the spectral clustering algorithm. The sense-making converts to a search based optimization problem as we built our model to maximize the probability of each node belonging to a neighborhood found depending on the likelihood of revisiting a node and of out-ward exploration.
高级语言： Jupyter Notebook
项目地址: git://github.com/tanishkasingh9/Node2Vec_DBLP_citation_graph.git
