A Java implementation of the FD-RMS algorithm in our paper "A Fully Dynamic Algorithm for k-Regret Minimizing Sets", which is available on https://arxiv.org/abs/2005.14493. All baseline algorithms we evaluate in our experiments are also available online. Please refer to https://users.cs.duke.edu/~ssintos/kRMS_SEA/ for the implementation of eps-Kernel, Greedy, and HittingSet; and https://www.cse.ust.hk/~raywong/code/sigmod18-sphere.zip for the implementation of DMM-Greedy, DMM-RRMS, GeoGreedy, and Sphere.
JDK 8+
- Apache Commons CLI 1.4, downloaded from https://mvnrepository.com/artifact/commons-cli/commons-cli/1.4
Data File: The first line of the data file specifies the dimensionality of the dataset; From the second line of the data file, each line represents one tuple in the dataset with different attributes split by a single space. Please refer to dataset/NBA/NBA.txt for an example.
Workload File: Each line of the workload file represents one tuple deletion from the dataset. Please refer to dataset/NBA/NBA_wl.txt for an example.
If you need other datasets used in our paper, feel free to contact Yanhao Wang. We do not include them in this repository because their sizes are too large.
To run FD-RMS with the default parameter settings:
$ runRMS.jar -d <dim> -f <dataset> -k <k> -r <r> -s <size>
<dim>: Integer, the dimensionality of the dataset
<dataset>: String, the name of the dataset, ["BB", "AQ", "CT", "Movie", "Indep", "AntiCor"]
<k>: Integer, the value of k in k-RMS
<r>: Integer, the size constraint of k-RMS
<size>: Integer, the size of the dataset, for Indep and AntiCor onlyTo run FD-RMS with varying the value of epsilon:
$ runRMS-eps.jar -d <dim> -f <dataset> -k <k> -r <r> -s <size>
<dim>: Integer, the dimensionality of the dataset
<dataset>: String, the name of the dataset, ["BB", "AQ", "CT", "Movie", "Indep", "AntiCor"]
<k>: Integer, the value of k in k-RMS
<r>: Integer, the size constraint of k-RMS
<size>: Integer, the size of the dataset, for Indep and AntiCor onlyTo run FD-RMS with customized parameter settings:
$ runRMS-inst.jar -d <dim> -e <epsilon> -i <input> -k <k> -m <M> -o <output> -r <r>
<dim>: Integer, the dimensionality of the dataset
<epsilon>: Float between 0 and 1, the value of epsilon in FD-RMS
<input>: String, the path of the data file
<k>: Integer, the value of k in k-RMS
<M>: Integer between 10 and 20 (M is set to 2^10 to 2^20 accordingly), the value of M in FD-RMS
<output>: String, the path of the result files
<r>: Integer, the size constraint of k-RMSIf there is any question, feel free to contact Yanhao Wang.