README.txt

This is the GraMi Source Release README
Last updated for GraMi on 11 March, 2014
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OVERVIEW:

GraMi is a novel framework for frequent subgraph mining in a single large 
graph, GraMi outperforms existing techniques by 2 orders of magnitudes. GraMi 
supports finding frequent subgraphs as well as frequent patterns, Compared to
subgraphs, patterns offer a more powerful version of matching that captures 
transitive interactions between graph nodes (like friend of a friend) which are
very common in modern applications. Also, GraMi supports user-defined 
structural and semantic constraints over the results, as well as approximate
results.

For more details, check our paper:
Mohammed Elseidy, Ehab Abdelhamid, Spiros Skiadopoulos, and Panos Kalnis. 
GRAMI: Frequent Subgraph and Pattern Mining in a Single Large Graph. PVLDB,
7(7):517-528, 2014.

CONTENTS:

    README ...................  This file
    LICENSE.txt ..............  License file (Open Source)
    build ....................  build GraMi java binary files
    grami ....................  script to run GraMi
    Datasets/ ................  Example graphs
    GRAMI_*/ .................  Directory containing GraMi sources


REQUIREMENTS:

Java JRE v1.6.0 or later

INSTALLATION:

- Uncompress Grami using any compression tool
- Build Java binaries using the "build" script file
- Run GraMi using "grami" script

EXAMPLES:

Run any of the following examples, results will be on "Output.txt". First line shows elapsed time in seconds. Second line has the number of frequent subgraphs, then frequent subgraphs are listed in the subsequent lines.

1- Show GraMi breif help:
	./grami -h

2- Find frequent subgraphs in the "mico" undirected graph, with minimum
frequency = 14000:
	./grami -f mico.lg -s 14000 -t 0 -p 0

3- Find frequent subgraphs in the "mico" undirected graph, with minimum
frequency = 9340 and approximation:
	./grami -f mico.lg -s 9340 -t 0 -p 0 -approxA 0.0002 -approxB=0

4- Find frequent patterns in the "citeseer" directed graph, with minimum
frequency = 160 and maximum distance bound (edge weight) = 200:
	./grami -f citeseer.lg -s 160 -t 1 -p 1 -d 200