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All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year Sort by creator [A → Z]' creator [Z → A]' publishing year ↑ (asc)' publishing year ↓ (desc)' title [A → Z]' title [Z → A]' Simple Search Hits 1 – 5 of 5 1 Homepage2Vec: Language-Agnostic Website Embedding and Classification ... Lugeon, Sylvain; Piccardi, Tiziano; West, Robert. - : arXiv, 2022 BASE Show details 2 Curlie Dataset - Language-agnostic Website Embedding and Classification ... Lugeon, Sylvain; Piccardi, Tiziano. - : figshare, 2022 BASE Show details 3 Curlie Dataset - Language-agnostic Website Embedding and Classification ... Lugeon, Sylvain; Piccardi, Tiziano. - : figshare, 2022 BASE Show details 4 Curlie Dataset - Language-agnostic Website Embedding and Classification ... Lugeon, Sylvain; Piccardi, Tiziano. - : figshare, 2022 BASE Show details 5 Curlie Dataset - Language-agnostic Website Embedding and Classification ... Lugeon, Sylvain; Piccardi, Tiziano. - : figshare, 2022 Abstract: **************** Full Curlie dataset **************** This dataset contains the URL scrapped from curlie.org alongside with their multilingual labels. The label correspond to the sub-category where the URL was referenced in Curlie. We also provide a mapping between english labels and labels from other languages for alignment. The URLs have been filtered to only contain homepages. Each distint URL is indexed with a unique identifier (uid). curlie.csv.gz > [url, uid, label, lang] x 2,275,150 samples mapping.json.gz > [english_label, matchings] x 35,946 labels **************** Processed Curlie dataset **************** You find here the data used to train Homepage2vec. URLs have been further filtered out: websites listed under the Regional top-category where dropped, as well as non-accessible websites. This filtering yields 1,018,207 valid URL. The labels are aligned across languages and reduced to the 14 top-categories (classes). Because a URL can belong to several classes, a binary vector is used. The ... Keyword: 170203 Knowledge Representation and Machine Learning; 80505 Web Technologies excl. Web Search; 80704 Information Retrieval and Web Search; Applied Computer Science; FOS Computer and information sciences; FOS Media and communications; FOS Psychology URL: https://figshare.com/articles/dataset/Curlie_Dataset_-_Language-agnostic_Website_Embedding_and_Classification/19406693/3 https://dx.doi.org/10.6084/m9.figshare.19406693.v3 BASE Hide details

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