0.This is experiment data for the following article:

@article{DBLP:journals/corr/abs-2110-06043,
  author    = {Gangli Liu},
  title     = {Topic Model Supervised by Understanding Map},
  journal   = {CoRR},
  volume    = {abs/2110.06043},
  year      = {2021},
  url       = {https://arxiv.org/abs/2110.06043},
  eprinttype = {arXiv},
  eprint    = {2110.06043},
  timestamp = {Fri, 22 Oct 2021 13:33:09 +0200},
  biburl    = {https://dblp.org/rec/journals/corr/abs-2110-06043.bib},
  bibsource = {dblp computer science bibliography, https://dblp.org}
}

1.  *.txt files are the data of Table 4 of the paper.

2. The top lines of all the *.txt files are contents of the artificial documents. Column names are  : "Topic", "Distance", "Topic-len", "alpha"/"Noise" , "doc concept-length", and "Votes counter".

3.Coding of file names of *.txt files see "Table 4: Discovered SCOM of six documents". "all_topic" means the candidate topic set is all the topics in a domain.

4.For the "300docs-mentioned-in-section3.2.xlsx" file, its name tells its contents.