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All Projects → oracle → pgx-samples

oracle / pgx-samples

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Applications using Parallel Graph AnalytiX (PGX) from Oracle Labs

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Sample applications using Parallel Graph AnalytiX (PGX)

Table of contents:

  1. Overview
  2. Download PGX
  3. Healthcare Fraud Detection
  4. Super Hero Network Analysis
  5. Graph-based ML applications using PgxML
    1. Graphlet representation
    2. Node representation
  6. Article Ranking
  7. Movie Recommendation
  8. Entity Linking
  9. Research Paper Classification

Overview

This repository contains a set of examples and use cases that illustrate the capabilities of PGX. Some of these use cases act as examples for some advanced functionalities, such as:

Download PGX

PGX is included as part of the Oracle Graph Server and Client product. A trial of Oracle Graph Server and Client can be downloaded from the Oracle Technology Network. PgxML and PGX Algorithm are available as of version 3.2.0 and released under the OTN license. Obtain the latest pgx-x.y.z-server zip file from the Oracle Graph Server and Client Downloads page and unzip it in the libs folder.

Healthcare Fraud Detection

The healthcare fraud detection example detects anomalies in medical transactions through a graph analysis procedure implemented in PGX. More details regarding this use-case are available here.

Super Hero Network Analysis

The Super Hero Network Analysis example describes how to combine computational graph analysis and graph pattern matching with PGX. More details regarding this use-case are available here.

Graph-based ML applications using PgxML

We provide two Graph-based ML applications, namely, Graphlet representation and Node representation.

Graphlet representation

This application demostrates how we can extract vector representation for each graphlet in a cluster of graphlets. For this application, we use the PG2Vec algorithm. More details regarding this application are available here.

Node representation

This application demonstrates how we can extract vector representation for each node in a graph. For this application, we use the DeepWalk algorithm. More details regarding this application are available here.

Article Ranking

This application demonstrates how ArticleRank could be employed to measure the influence of journal articles. More details regarding this application are available here.

Movie Recommendation

This application demonstrates how Matrix Factorization could be employed to recommend movies to users. More details regarding this application are available here.

Entity Linking

Entity Linking allows to connect Named Entities (for example, names of famous people) to their Wikipedia/DBpedia page. This application leverages vertex embeddings to provide high-quality results. More details available here and in our paper.

Research Paper Classification

This application demonstrates how graph data can be used to enhance classification performance of a research paper classifier. More details regarding this application are available here.

Note that the project description data, including the texts, logos, images, and/or trademarks, for each open source project belongs to its rightful owner. If you wish to add or remove any projects, please contact us at [email protected].