|
1 | | -# Sample applications using Parallel Graph AnalytiX (PGX) |
| 1 | +# PGX Samples |
2 | 2 |
|
3 | | -## Table of contents: |
4 | | - |
5 | | -1. [Overview](#overview) |
6 | | -2. [Download PGX](#pgx-download) |
7 | | -3. [Healthcare Fraud Detection](#healthcare-fraud-detection) |
8 | | -4. [Super Hero Network Analysis](#super-hero-network-analysis) |
9 | | -5. [Graph-based ML applications using PgxML](#pgxml-apps) |
10 | | - 1. [Graphlet representation](#graphlet-representation) |
11 | | - 2. [Node representation](#node-representation) |
12 | | -6. [Article Ranking](#article-ranking) |
13 | | -7. [Movie Recommendation](#movie-recommender) |
14 | | -8. [Entity Linking](#entity-linking) |
15 | | -9. [Research Paper Classification](#paper-classification) |
16 | | - |
17 | | -**** |
18 | | - |
19 | | -## Overview <a name="overview"></a> |
20 | | -This repository contains a set of examples and use cases that illustrate the capabilities of [PGX](https://www.oracle.com/technetwork/oracle-labs/parallel-graph-analytix). |
21 | | -Some of these use cases act as examples for some advanced functionalities, such as: |
22 | | - |
23 | | -* The [PgxML library](https://docs.oracle.com/cd/E56133_01/latest/prog-guides/mllib/index.html), for Graph-based ML |
24 | | -* The [PGX Algorithm](https://docs.oracle.com/cd/E56133_01/latest/reference/analytics/pgx-algorithm.html) API, a high-level DSL for developing optimized graph algorithms. |
25 | | - |
26 | | -## Download PGX <a name="pgx-download"></a> |
27 | | -PGX is included as part of the Oracle Graph Server and Client product. |
28 | | -A trial of Oracle Graph Server and Client can be downloaded from the [Oracle Technology Network](https://www.oracle.com/database/technologies/spatialandgraph/property-graph-features/graph-server-and-client/graph-server-and-client-downloads.html). |
29 | | -PgxML and PGX Algorithm are available as of version 3.2.0 and released under the [OTN license](https://www.oracle.com/technetwork/licenses/standard-license-152015.html). |
30 | | -Obtain the latest `pgx-x.y.z-server` zip file from the [Oracle Graph Server and Client Downloads page](https://www.oracle.com/database/technologies/spatialandgraph/property-graph-features/graph-server-and-client/graph-server-and-client-downloads.html) and unzip it in the `libs` folder. |
| 3 | +PGX (Parallel Graph AnalytiX) is a graph toolkit that provides a graph query language, optimized analytics algorithms, and machine learning support to extract insights hidden in the connections across datasets at high-performance and extreme scale. |
31 | 4 |
|
32 | | -## Healthcare Fraud Detection <a name="healthcare-fraud-detection"></a> |
33 | | -The healthcare fraud detection example detects anomalies in medical transactions through a graph analysis procedure implemented in PGX. |
34 | | -More details regarding this use-case are available [here](healthcare/README.md). |
| 5 | +While graphs have become ubiquitous nowadays as the backbone of multiple applications - from search engines and recommender systems to intelligent chatbots, PGX enables fast graph analysis on such industry-scale graphs (with trillions of edges) to reveal latent information between linked entities. |
35 | 6 |
|
36 | | -## Super Hero Network Analysis <a name="super-hero-network-analysis"></a> |
37 | | -The Super Hero Network Analysis example describes how to combine computational graph analysis and graph pattern matching with PGX. |
38 | | -More details regarding this use-case are available [here](superhero/README.md). |
39 | | - |
40 | | -## Graph-based ML applications using PgxML <a name="pgxml-apps"></a> |
41 | | -We provide two Graph-based ML applications, namely, `Graphlet representation` and `Node representation`. |
42 | | - |
43 | | -### Graphlet representation <a name="graphlet-representation"></a> |
44 | | -This application demostrates how we can extract vector representation for each graphlet in a cluster of graphlets. |
45 | | -For this application, we use the [PG2Vec](https://docs.oracle.com/cd/E56133_01/latest/prog-guides/mllib/pg2vec.html) algorithm. |
46 | | -More details regarding this application are available [here](graphlet-representation/README.md). |
47 | | - |
48 | | -### Node representation <a name="node-representation"></a> |
49 | | -This application demonstrates how we can extract vector representation for each node in a graph. |
50 | | -For this application, we use the [DeepWalk](https://docs.oracle.com/cd/E56133_01/latest/prog-guides/mllib/deepwalk.html) algorithm. |
51 | | -More details regarding this application are available [here](node-representation/README.md). |
52 | | - |
53 | | -## Article Ranking <a name="article-ranking"></a> |
54 | | -This application demonstrates how ArticleRank could be employed to measure the influence of journal articles. |
55 | | -More details regarding this application are available [here](article-ranking/README.md). |
| 7 | +## Table of contents: |
56 | 8 |
|
57 | | -## Movie Recommendation <a name="movie-recommendation"></a> |
58 | | -This application demonstrates how Matrix Factorization could be employed to recommend movies to users. |
59 | | -More details regarding this application are available [here](movie-recommendation/README.md). |
| 9 | +- [Built-in Algorithms](./built-in-algorithms/README.md) |
60 | 10 |
|
61 | | -## Entity Linking <a name="entity-linking"></a> |
62 | | -Entity Linking allows to connect Named Entities (for example, names of famous people) to their Wikipedia/DBpedia page. |
63 | | - This application leverages vertex embeddings to provide high-quality results. More details available [here](entity-linking/README.md) and in our [paper](https://dl.acm.org/citation.cfm?doid=3327964.3328499). |
64 | 11 |
|
65 | | -## Research Paper Classification <a name="paper-classification"></a> |
66 | | -This application demonstrates how graph data can be used to enhance classification performance of a research paper classifier. |
67 | | -More details regarding this application are available [here](paper-classification/README.md). |
0 commit comments