{"url":"/dataset/experiment-data-for-um-s-tm","name":"Experiment-data-for-UM-S-TM","full_name":null,"description_markdown":"0.This is experiment data for the following article:\r\n@misc{liu2021topic,\r\n      title={Topic Model Supervised by Understanding Map}, \r\n      author={Gangli Liu},\r\n      year={2021},\r\n      eprint={2110.06043},\r\n      archivePrefix={arXiv},\r\n      primaryClass={cs.CL}\r\n}\r\n\r\n1.  *.txt files are the data of Table 4 of the paper.\r\n\r\n2. 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\".\r\n\r\n3.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.\r\n\r\n4.For the \"300docs-mentioned-in-section3.2.xlsx\" file, its name tells its contents.","description_withheld":null,"homepage":"https://github.com/mike-liuliu/Data-for-UM-S-TM","introduced_date":"2021-10-12","introduced_date_note":null,"introduced_by":{"paper":"/paper/topic-model-supervised-by-understanding-map","title":"Topic Model Supervised by Understanding Map","first_author":"Gangli Liu","url":null},"license":null,"modalities":[],"tasks":[],"languages":[],"variants":["Experiment-data-for-UM-S-TM"],"data_loaders":[],"num_papers_in_archive":1,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[],"papers_with_a_benchmark_row":[],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":0,"samples_harvested":0,"samples_ran":0,"samples_unverified":0,"pointer_only_for_licence":0,"papers_with_no_sample_that_ran":0,"note":"the per-paper counts above, summed; not a rate"},"papers_note":"The archive never published its papers-using-dataset list; these are papers with a leaderboard row on this dataset's benchmarks."}