English word2vec embeddings trained on OpenSubtitles Part 10
收藏资源简介:
This dataset contains the subs2vec embeddings for English, as presented in https://zenodo.org/records/17243814. The embeddings were trained on large-scale subtitle corpora and represent semantic vector spaces derived from naturalistic language use in films and television from the OpenSubtitles 2018 datasets: https://opus.nlpl.eu/OpenSubtitles/corpus/version/OpenSubtitles. For this language, we provide all embedding variants explored in the study. Specifically, the dataset includes vectors generated under different combinations of: Dimensionality: multiple vector sizes (e.g., 100, 200, 300, …) Window size: varying context windows (e.g., 2, 5, 10, …) Each file corresponds to a unique configuration (dimension × window size). Each file contains the vocabulary for that language (column 1) and then the embedding values (columns 2 through dimension size + 1). If you use this dataset, please cite: Manuscript: https://doi.org/10.5281/zenodo.17243812 Data: This Zenodo dataset (using the DOI provided here) sha256sum hashes: en_500_6_cbow_wxd.csv.bz2 c9f04ca963f2155e407be659c8a284f15a685306dbe0d3acd8e5129994d3d1ef en_500_6_sg_wxd.csv.bz2 c882b4f1b6745b84a582d86cb2f6e5cd121ddbad62a756a546d5ed8ee95dec2a
本数据集收录英语语言的subs2vec嵌入向量(subs2vec embeddings),相关详情可参见https://zenodo.org/records/17243814。该嵌入向量基于大规模字幕语料库训练得到,其语义向量空间源自OpenSubtitles 2018数据集(OpenSubtitles 2018)中影视与剧集的自然语言使用场景,相关语料库链接为:https://opus.nlpl.eu/OpenSubtitles/corpus/version/OpenSubtitles。 针对该语言,我们提供了本研究中探索的全部嵌入变体。具体而言,本数据集包含基于不同参数组合生成的向量: - 维度(Dimensionality):多种向量维度规格(如100、200、300等) - 窗口大小(Window size):不同的上下文窗口尺寸(如2、5、10等) 每个文件对应一组唯一的配置组合(维度 × 窗口大小)。 每个文件包含该语言的词汇表(第1列)以及对应的嵌入值(第2列至第维度大小+1列)。 若使用本数据集,请引用以下文献: 学术论文:https://doi.org/10.5281/zenodo.17243812 数据集:本Zenodo数据集(使用此处提供的DOI) sha256sum哈希值: en_500_6_cbow_wxd.csv.bz2 c9f04ca963f2155e407be659c8a284f15a685306dbe0d3acd8e5129994d3d1ef en_500_6_sg_wxd.csv.bz2 c882b4f1b6745b84a582d86cb2f6e5cd121ddbad62a756a546d5ed8ee95dec2a



