TopicNet/PostNauka
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… See the full description on the dataset page: https://huggingface.co/datasets/TopicNet/PostNauka.
PostNauka
Some measurable characteristics of the dataset:
- D — number of documents
- <modality name> W — modality dictionary size (number of unique tokens)
- <modality name> len D — average document length in modality tokens (number of tokens)
- <modality name> len D uniq — average document length in unique modality tokens (number of unique tokens)
The @snippet modality is a piece of raw text designed to display top documents.
Information about document lengths in modality tokens:
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 🙃)
