32 datasets found

Individual text corpora (ICs) were generated from 214 participants with a mean number of 5 million word tokens.

The dataset used in the paper is a collection of 1.1M tweets from Twitter, with approximately 3000 tweets per user from various domains such as politics, sports, entertainment,...

Radiology reports dataset is used to test the proposed Hierarchical Latent Word Clustering algorithm.

NIPS dataset is used to test the proposed Hierarchical Latent Word Clustering algorithm.

Hierarchical Latent Word Clustering dataset is used to test the proposed Hierarchical Latent Word Clustering algorithm.

Opinion mining and sentiment analysis dataset

The GoEmotions dataset, a collection of 58k Reddit comments labeled according to the publisher affect from a taxonomy of 28 emotions.

Probase is a probabilistic knowledge base and it contains millions of entities and concepts. One of the advantages of Probase is that in comparison with the well-known knowledge...

The ACL Anthology dataset contains 21,212 papers, 17,792 authors, 342 venues, and 110,975 citations.

The Twitter Dataset is a collection of tweets annotated with Plutchik's emotions, consisting of tweets in three different languages: English, Dutch, and German.

The ACL Anthology dataset contains papers on natural language processing, including citation patterns, authorship, and language use over time.

The Penn Tree Bank dataset is a corpus split into a training, validation and testing set of 929k words, a validation set of 73k words, and a test set of 82k words. The...

MS MARCO V1 corpus

The dataset used in the paper is a subset of the Wikipedia corpus, consisting of 7500 English Wikipedia articles belonging to one of the following categories: People, Cities,...

Matrix factorization (MF) and Autoencoder (AE) are among the most successful approaches of unsupervised learning.

The dataset used in the paper is the Wikipedia dataset, which contains over six million English Wikipedia articles with a full-text field associated with 50 training queries...

The dataset used in the paper is the bookcorpus dataset.

The Yelp review dataset contains hotel and restaurant reviews filtered (spam) and recommended (legitimate) by Yelp.

Bilingual word embeddings from parallel and non-parallel corpora for cross-language text classification

The Reddit Million User Dataset is a collection of 4 million comments from 400k different Reddit users.