metadata
language:
- ru
multilinguality:
- monolingual
license: other
license_name: topicnet
license_link: >-
https://github.com/machine-intelligence-laboratory/TopicNet/blob/master/LICENSE.txt
configs:
- config_name: bag-of-words
default: true
data_files:
- split: train
path: data/bow/postnauka.csv.gz
- config_name: natural-order-of-words
data_files:
- split: train
path: data/noow/postnauka.csv.gz
task_categories:
- text-classification
task_ids:
- topic-classification
- multi-class-classification
- multi-label-classification
tags:
- topic-modeling
- topic-modelling
- text-clustering
- multimodal-data
- multimodal-learning
- modalities
- document-representation
PostNauka
Some measurable characteristics of the dataset:
- D — number of documents
- W — modality dictionary size (number of unique tokens)
- len D — average document length in modality tokens (number of tokens)
- len D uniq — average document length in unique modality tokens (number of unique tokens)
| D | @title W | @title len D | @title len D uniq | @2gramm W | @2gramm len D | @2gramm len D uniq | @3gramm W | @3gramm len D | @3gramm len D uniq | @snippet W | @snippet len D | @snippet len D uniq | @word W | @word len D | @word len D uniq | @post_tag W | @post_tag len D | @post_tag len D uniq | @author W | @author len D | @author len D uniq | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| value | 3404 | 13546 | 3.97944 | 3.98002 | 163289 | 47.9697 | 37.0029 | 5848 | 1.71798 | 1.30288 | 46033 | 13.5232 | 13.5256 | 1.43373e+06 | 421.189 | 254.58 | 18031 | 5.297 | 5.297 | 3685 | 1.08255 | 1.08255 |
The @snippet modality is a piece of raw text designed to display top documents.
Information about document lengths in modality tokens:
| len_total@title | len_total@2gramm | len_total@3gramm | len_total@snippet | len_total@word | len_total@post_tag | len_total@author | len_uniq@title | len_uniq@2gramm | len_uniq@3gramm | len_uniq@snippet | len_uniq@word | len_uniq@post_tag | len_uniq@author | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| mean | 3.98002 | 47.9697 | 1.71798 | 13.5244 | 421.189 | 5.297 | 1.08255 | 3.98002 | 37.0029 | 1.30288 | 13.5256 | 254.58 | 5.297 | 1.08255 |
| std | 2.21452 | 49.9748 | 3.07432 | 3.0559 | 482.422 | 2.01979 | 0.413483 | 2.21452 | 35.4885 | 1.81957 | 3.05377 | 249.288 | 2.01979 | 0.413483 |
| min | 1 | 0 | 0 | 5 | 3 | 1 | 0 | 1 | 0 | 0 | 5 | 3 | 1 | 0 |
| 25% | 2 | 15 | 0 | 12 | 106 | 4 | 1 | 2 | 13 | 0 | 12 | 80 | 4 | 1 |
| 50% | 3.5 | 33 | 1 | 13 | 294 | 5 | 1 | 3.5 | 27 | 1 | 13 | 197 | 5 | 1 |
| 75% | 5 | 67 | 2 | 15 | 563 | 6 | 1 | 5 | 52 | 2 | 15 | 343 | 6 | 1 |
| max | 22 | 778 | 69 | 28 | 4892 | 18 | 4 | 22 | 444 | 27 | 28 | 2277 | 18 | 4 |
There exists a reference "gold-standard" topic model for 19 + 1 (background) topics. Information about topics is available for the natural word order version of the dataset. (At the same time, bag-of-words dataset with @snippet-s includes the same documents as the dataset with a natural order of words, but under different names — and information about the correspondence of document names, alas, is lost 🙃)