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--- |
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language: |
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- ru |
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multilinguality: |
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- monolingual |
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license: other |
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license_name: topicnet |
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license_link: >- |
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https://github.com/machine-intelligence-laboratory/TopicNet/blob/master/LICENSE.txt |
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configs: |
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- config_name: "bag-of-words" |
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default: true |
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data_files: |
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- split: train |
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path: "data/bow/postnauka.csv.gz" |
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- config_name: "natural-order-of-words" |
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data_files: |
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- split: train |
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path: "data/noow/postnauka.csv.gz" |
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task_categories: |
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- text-classification |
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task_ids: |
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- topic-classification |
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- multi-class-classification |
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- multi-label-classification |
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tags: |
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- topic-modeling |
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- topic-modelling |
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- text-clustering |
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- multimodal-data |
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- multimodal-learning |
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- modalities |
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- document-representation |
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--- |
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# PostNauka |
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Some measurable characteristics of the dataset: |
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* D — number of documents |
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* <modality name> W — modality dictionary size (number of unique tokens) |
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* <modality name> len D — average document length in modality tokens (number of tokens) |
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* <modality name> len D uniq — average document length in unique modality tokens (number of unique tokens) |
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| | 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 | |
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|:------|------------:|------------------:|----------------------:|---------------------------:|-------------------:|-----------------------:|----------------------------:|-------------------:|-----------------------:|----------------------------:|--------------------:|------------------------:|-----------------------------:|-----------------:|---------------------:|--------------------------:|---------------------:|-------------------------:|------------------------------:|-------------------:|-----------------------:|----------------------------:| |
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| 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 | |
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The `@snippet` modality is a piece of raw text designed to display top documents. |
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Information about document lengths in modality tokens: |
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| | 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 | |
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|:-----|------------------:|-------------------:|-------------------:|--------------------:|-----------------:|---------------------:|-------------------:|-----------------:|------------------:|------------------:|-------------------:|----------------:|--------------------:|------------------:| |
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| 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 | |
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| 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 | |
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| min | 1 | 0 | 0 | 5 | 3 | 1 | 0 | 1 | 0 | 0 | 5 | 3 | 1 | 0 | |
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| 25% | 2 | 15 | 0 | 12 | 106 | 4 | 1 | 2 | 13 | 0 | 12 | 80 | 4 | 1 | |
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| 50% | 3.5 | 33 | 1 | 13 | 294 | 5 | 1 | 3.5 | 27 | 1 | 13 | 197 | 5 | 1 | |
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| 75% | 5 | 67 | 2 | 15 | 563 | 6 | 1 | 5 | 52 | 2 | 15 | 343 | 6 | 1 | |
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| max | 22 | 778 | 69 | 28 | 4892 | 18 | 4 | 22 | 444 | 27 | 28 | 2277 | 18 | 4 | |
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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](https://huggingface.co/datasets/TopicNet/PostNauka/tree/main/data/noow). (At the same time, [bag-of-words dataset](https://huggingface.co/datasets/TopicNet/PostNauka/tree/main/data/bow) 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 🙃) |
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