Property graph inference (PG)

To cite us, use the following BibTex references:

@inproceedings{DBLP:conf/edbt/BonifatiDM22,
  author    = {Angela Bonifati and
               Stefania Dumbrava and
               Nicolas Mir},
  title     = {Hierarchical Clustering for Property Graph Schema Discovery},
  booktitle = {{EDBT}},
  pages     = {2:449--2:453},
  publisher = {OpenProceedings.org},
  year      = {2022}
}

About the project

This python project infers a schema from a PG stored in Neo4j. This method uses a clustering method, a Bayesian Gaussian Mixture Model, to gather similar nodes together. It is meant to deal with both unlabeled and labeled nodes, properties, multi-labeled nodes, overlapping types.

Dependencies

Use pip to install these 3 python modules :

termcolor
hdbscan==0.8.27
neo4j==4.3.4

Neo4j :

Neo4j Desktop 1.4.8
Add local DBMS with a Neo4j version of 3.5.3 or more

Imports for LDBC, fib25 and mb6

Download the csv files from the databases folder.

Follow these instructions to import LDBC, fib25 or mb6 (steps 1 to 6 are already done): https://github.com/connectome-neuprint/neuPrint/blob/master/neo4j_desktop_load.md

At step 10 of the previous page for LDBC and fib25 you will need a command to load the data.

For LDBC :

./bin/neo4j-admin import --database=ldbc.db --delimiter='|' --nodes=Comment=import/comment_0_0.csv --nodes=Forum=import/forum_0_0.csv --nodes=Person=import/person_0_0.csv --nodes=Post=import/post_0_0.csv --nodes=Place=import/place_0_0.csv --nodes=Organisation=import/organisation_0_0.csv --nodes=TagClass=import/tagclass_0_0.csv --nodes=Tag=import/tag_0_0.csv --relationships=HAS_CREATOR=import/comment_hasCreator_person_0_0.csv --relationships=HAS_TAG=import/comment_hasTag_tag_0_0.csv --relationships=IS_LOCATED_IN=import/comment_isLocatedIn_place_0_0.csv --relationships=REPLY_OF=import/comment_replyOf_comment_0_0.csv --relationships=REPLY_OF=import/comment_replyOf_post_0_0.csv --relationships=CONTAINER_OF=import/forum_containerOf_post_0_0.csv --relationships=HAS_MEMBER=import/forum_hasMember_person_0_0.csv --relationships=HAS_MODERATOR=import/forum_hasModerator_person_0_0.csv --relationships=HAS_TAG=import/forum_hasTag_tag_0_0.csv --relationships=HAS_INTEREST=import/person_hasInterest_tag_0_0.csv --relationships=IS_LOCATED_IN=import/person_isLocatedIn_place_0_0.csv --relationships=KNOWS=import/person_knows_person_0_0.csv --relationships=LIKES=import/person_likes_comment_0_0.csv --relationships=LIKES=import/person_likes_post_0_0.csv --relationships=STUDIES_AT=import/person_studyAt_organisation_0_0.csv --relationships=WORKS_AT=import/person_workAt_organisation_0_0.csv --relationships=HAS_CREATOR=import/post_hasCreator_person_0_0.csv --relationships=HAS_TAG=import/post_hasTag_tag_0_0.csv --relationships=IS_LOCATED_IN=import/post_isLocatedIn_place_0_0.csv --relationships=IS_LOCATED_IN=import/organisation_isLocatedIn_place_0_0.csv --relationships=IS_PART_OF=import/place_isPartOf_place_0_0.csv --relationships=HAS_TYPE=import/tag_hasType_tagclass_0_0.csv --relationships=IS_SUBCLASS_OF=import/tagclass_isSubclassOf_tagclass_0_0.csv

For fib25 :

/bin/neo4j-admin import --database=fib25.db --nodes=import/Neuprint_Meta_fib25.csv --nodes=import/Neuprint_Neurons_fib25.csv --relationships=ConnectsTo=import/Neuprint_Neuron_Connections_fib25.csv --nodes=import/Neuprint_SynapseSet_fib25.csv --relationships=ConnectsTo=import/Neuprint_SynapseSet_to_SynapseSet_fib25.csv --relationships=Contains=import/Neuprint_Neuron_to_SynapseSet_fib25.csv --nodes=import/Neuprint_Synapses_fib25.csv --relationships=SynapsesTo=import/Neuprint_Synapse_Connections_fib25.csv --relationships=Contains=import/Neuprint_SynapseSet_to_Synapses_fib25.csv

Launch the database.

The Covid-19 graph codebase is accessible here: Cord-19.

Running the project

python3 cluster_script.py
Enter Neo4j database info :

Name of the database: "any name"
Neo4j bolt address: bolt://localhost:7687 (for ldbc, fib25 or mb6) | bolt://db.covidgraph.org:7687 (for Covid19)
Neo4j username: "neo4j by default, otherwise your DBMS username"
Neo4j password : "your DBMS password"

protectione055 / pg-schemainference