Supervised_Link_Prediction_Using_Spark_and_Neo4j

university-project

A project which involves analysis of Authorship graph data from Microsoft academic graph. In this project we calculate different graph features using temporal parameters of the authors and tried different classifiers. The final aim is to predict the link or coauthorsip possibility between two authors based on topological graph features and also find out the feasibility of performing this task on Neo4j and Spark

How to download and setup Supervised_Link_Prediction_Using_Spark_and_Neo4j

Open terminal and run command

git clone https://github.com/surajsrivathsa/Supervised_Link_Prediction_Using_Spark_and_Neo4j.git

git clone is used to create a copy or clone of Supervised_Link_Prediction_Using_Spark_and_Neo4j repositories. You pass git clone a repository URL.
it supports a few different network protocols and corresponding URL formats.

Also you may download zip file with Supervised_Link_Prediction_Using_Spark_and_Neo4j https://github.com/surajsrivathsa/Supervised_Link_Prediction_Using_Spark_and_Neo4j/archive/master.zip

Or simply clone Supervised_Link_Prediction_Using_Spark_and_Neo4j with SSH

[email protected]:surajsrivathsa/Supervised_Link_Prediction_Using_Spark_and_Neo4j.git

If you have some problems with Supervised_Link_Prediction_Using_Spark_and_Neo4j

You may open issue on Supervised_Link_Prediction_Using_Spark_and_Neo4j support forum (system) here: https://github.com/surajsrivathsa/Supervised_Link_Prediction_Using_Spark_and_Neo4j/issues

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