Scaling Ecommerce Graphs

This folder contains all the datasets used for the performance evaluation of the MINE GRAPH RULE operator proposed in the paper "MINE GRAPH RULE: A New GQL Operator for Mining Association Rules in Property Graph Databases".

Each folder contains the following files used to create a property graph in Neo4j with a fixed schema mimicking an e-commerce site.

Item.csv - contains the data for the Item nodes.

Person.csv - contains the data for the Person nodes.

Category.csv - contains the data for the Category nodes.

FOLLOW.csv - contains the data for the FOLLOW relationships from Person to Person nodes.

BUY.csv - contains the data for the BUY relationships from Person to Item nodes.

RECOMMEND.csv - contains the data for the RECOMMEND relationship from Person to Item nodes.

OF.csv - contains the data for the OF relationship from Item to Category nodes.

The folders contain various graph instances with differing dimensions, and each folder is named to reflect its defining features. The features in the name are given in this order:

Total number of nodes within the graph.

Ratio of the number of Person nodes over the nodes with other labels.

Probability of having a relationship FOLLOW between two Person nodes.

Probability of having a relationship BUY between a Person node and an Item node.

Probability of having a relationship RECOMMEND between a Person node and an Item node.

(Example: the folder 10000_0.5_0.0005_0.1_0.0005_dataset contains files of a graph with 10000 nodes, of which half of them are Person nodes, 0.0005 is the probability of having a relationship FOLLOW between two Person nodes, 0.1 is the probability of having a relationship BUY between a Person node and an Item node, and 0.0005 is the probability of having a relationship RECOMMEND between a Person node and an Item node).