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carti-rank

Impelementation of Carti-Rank algorithm. See http://adrem.uantwerpen.be/cartirank for more information.

Carti-Rank: Finding Subspace Clusters using Ranked Neighborhoods

This project is an implementation of the Carti-Rank algorithm. The details can be found in http://adrem.uantwerpen.be/cartirank .

Application

Carti-Rank is packaged as a runnable .jar file (carti-rank.jar). You can run the application on command line with the commands,

java -jar carti-rank.jar data-file theta minlen

Input

Carti-Rank accepts parameters as command line arguments in a specified order.

  • data-file: Path to the multi dimensional datafile. Please find the properties of the data file below.
  • k: Parameter for the tile mining.
  • minsup: Minimum length for the cluster.

About the data file:

  • it includes space separated real values,
  • each row represents an instance,
  • each column represents a feature/dimension,
  • does not include a(ny) header row(s),
  • all instances have the same number of features,
  • there are no missing values,
  • the real values formatted in the USA locale (use . as decimal separator)

Output

Carti-Rank outputs the found clusters to the standard output. Each line of output represents a subspace cluster. Output format:

Size of the cluster - Dimensions of the cluster - Objects of the cluster

For example, 10 - 1 2 6 - 0 1 2 3 4 5 6 7 8 9 means a cluster is detected at 1st, 2nd and 6th subspaces and it has '10' objects, i.e., 0 1 2 3 4 5 6 7 8 9

Example

java -jar carti-rank.jar ns25.mime 25 20

Datasets

Datasets that are used in the original paper can be found [here][datasets].

Building the Application

Get the latest source code from https://gitlab.com/adrem/carti-rank by using the command

git clone https://gitlab.com/adrem/carti-rank.git

This implementation uses Apache Maven for dependency management and building. To create an executable .jar file, execute the following command

mvn clean compile assembly:single

An executable jar file will be created in target directory. See above for running instructions.

Contact

For more information you can visit http://adrem.uantwerpen.be/cartirank or send an email to Emin Aksehirli emin.aksehirli@gmail.com.