NAISC - Automated Linking Tool

'Naisc' means 'links' in Irish and is pronounced 'nashk'.

Installation

Naisc can be installed with Gradle, to compile and run the system run the following:

./gradlew jarWithDeps

Meas - Meas Evaluation and Analysis Suite

For developing models and training there is a web application that can be built by the following

./gradlew meas

The Web interface will be available at http://localhost:8080

Alternatively you may download a precompiled version from https://john.mccr.ae/naisc/naisc-meas-all-1.1.jar and run it wtih

java -jar naisc-meas-all-1.1.jar

ELEXIS Interface

The linking interface for use with ELEXIS can be started with

./gradlew bootRun

It will be available at http://localhost:8080. More information about how to use this service is available at https://elexis-eu.github.io/elexis-rest/linking.html

Command line operation

Naisc can be operated from the command line with the following script

./naisc.sh left.rdf right.rdf -c config.json -o alignment.rdf

This will output the alignment using the configuration to alignment.rdf

Offline training can be created using the training script, the dataset should be available under datasets/

./train.sh dataset -c config.json

Command line options

For linking (naisc.sh)

Option       Description
------       -----------
-c <File>    The configuration to use
-f <File>    Dump features
-n <Double>  Negative Sampling rate (number of
               negative examples/positive example)
-q           Quiet (suppress output)

For training (train.sh)

Option       Description
------       -----------
-c <File>    The configuration to use
-f <File>    Dump features
-n <Double>  Negative Sampling rate (number of
               negative examples/positive example)
-q           Quiet (suppress output)

Basic configurations

The following basic configurations are available:

1. config/jaccard.json: A simple Jaccard based string similarity
2. config/string-match.json: Uses string similarity metrics only
3. config/auto.json: The general purpose linker

Documentation

Javadoc for Naisc is available at https://uld.pages.insight-centre.org/naisc

There is an overview of the tool available here

For extending Naisc with new services please see the guide here

There is a quick video introduction on YouTube: