GoldMiner is a tool for Statistical Schema Induction as proposed by Völker and Niepert [1] and extended by Fleischhacker and Völker [2][3].
[1] Johanna Völker and Mathias Niepert. Statistical Schema Induction. The Semantic Web: Research and Applications : 8th Extended Semantic Web Conference, ESWC 2011, Heraklion, Crete, Greece, Proceedings, Part I, 2011.
[2] Daniel Fleischhacker and Johanna Völker. Inductive Learning of Disjointness Axioms. On the Move to Meaningful Internet Systems: OTM 2011 : Confederated International Conferences: CoopIS, DOA-SVI, and ODBASE 2011, Hersonissos, Crete, Greece, Proceedings, Part II, 2011.
[3] Daniel Fleischhacker, Johanna Völker and Heiner Stuckenschmidt. Mining RDF Data for Property Axioms. On the Move to Meaningful Internet Systems: OTM 2012 : Confederated International Conferences: CoopIS, DOA-SVI, and ODBASE 2012. Proceedings, Part II, 2012.
If you downloaded the source source of GoldMiner, you have to build the binary distribution first. The build process is based on Apache Maven (http://maven.apache.org). After having installed Maven, change into the GoldMiner source directory and use "mvn package" to start the build process. Have a look at the target/ folder which contains the gold-miner-VERSION-jar-with-dependencies.jar which is the one you would like to use most probably.
In the following we use goldminer.jar to refer to the name of the GoldMiner JAR. For calling GoldMiner, you have to replace goldminer.jar by the correct file name or rename your jar file to goldminer.jar.
Call gold miner using the genconfig command java -jar goldminer.jar genconfig which generates the config files miner.properties and axioms.properties in the current directory. Adapt miner.properties to your environment and choose the axiom types you want to generate by setting them to true in axioms.properties. The axioms types not to generate have to be set to false.
Running GoldMiner includes three phases. In the first phase, GoldMiner inspects the ontology for concepts and properties, the SPARQL endpoint for instances and generates the transaction tables required for the currently configured axiom types. This phase might take longer depending on the performance of your SPARQL endpoint. You can start the generation phase using java -jar goldminer.jar generate
The next step uses the Borgelt apriori miner to generate association rules and is started by java -jar goldminer.jar mine
In the final step, the association rules are parsed and the ontology is enriched with the resulting axioms. Use java -jar goldminer.jar parse to start this phase.
If you want to re-run GoldMiner completely you either have to empty all directories which contain results from previous runs or empty the checkpoints/ directory in your transaction_tables directory (as defined in the miner.properties config file) since GoldMiner uses this directory to store its progress.
Copyright (C) 2011-2014 Johanna Völker, Mathias Niepert, Daniel Fleischhacker
This program is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version.
This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details.
You should have received a copy of the GNU General Public License along with this program. If not, see http://www.gnu.org/licenses/.