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GitHub / surajsrivathsa / Supervised_Link_Prediction_Using_Spark_and_Neo4j

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

JSON API: http://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/surajsrivathsa%2FSupervised_Link_Prediction_Using_Spark_and_Neo4j

Stars: 5
Forks: 4
Open issues: 0

License: None
Language: Scala
Size: 15.8 MB
Dependencies parsed at: Pending

Created at: over 5 years ago
Updated at: almost 2 years ago
Pushed at: almost 5 years ago
Last synced at: over 1 year ago

Topics: graphframes, graphx, neo4j, spark, spark-mllib, university-project

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