To reproduce all the results of the paper, just do the following:
download the ssc-cosine.zip file and uncompress it
download all the .mat files and store them in a subfolder called Data
run script_all.m from the parent folder in MATLAB.
Structure of the package
Main function: ssc-cosine.m
Scripts used to reproduce the individual results reported in the ICPR18 paper:
script_20news_processing: This script processes the raw 20newsgroups data (Matlab bydate version) downloadable from http://qwone.com/~jason/20Newsgroups/ (executing this script is optional as the processed data has been provided).
script_20news_results.m: Table I
script_20news_insights.m: Figure 2
script_20news_alpha.m: Figure 3
script_tdt2_top30_results.m: Figure 4
script_digits_results.m: Table II
Scripts used to reproduce the results reported in the short paper:
script_20news_alpha_scalable3.m: Figure 1
script_tdt2_top30_DMt.m: Figure 2
Required external functions:
The kmeans.m function, available through the Statistics and Machine Learning Toolbox, is needed by the main function ssc-cosine.m. If that toolbox is not available in the computer, then one may use instead a substitute kmeans implementation, such as the litekmeans.m function available at http://www.cad.zju.edu.cn/home/dengcai/Data/Clustering.html.
The bestMap.m function, available also on the above webpage, is needed by the scripts for finding the best match between the ground-truth labels and the group labels obtained by the function ssc-cosine.m, in order to compute the clustering accuracy.
For your convenience, the litekmeans.m and bestMap.m functions have been included in this repository.
General info
[x] Conference: ICPR 2018 & RRPR18 (id 09)
[x] Papers title: Scalable Spectral Clustering with Cosine Similarity
[x] Source paper: paper S11
[x] GitHub repo: https://github.com/glsjsu/rprr2018
[x] Submission date: 5/08/2018
[ ] Platform:
[x] Language: MATLAB
[x] Results to be reproduced:
[x] Reproduction main step instructions: (from [Readme]. (https://github.com/glsjsu/rprr2018/blob/master/README.md) file)
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