21 to 30 of 55 Results
Aug 19, 2019 -
Negative Sampling for Learning Knowledge Graph Embeddings
ZIP Archive - 19.4 KB -
MD5: d2e8ac74e3f20d2cdec2225962c7e2f0
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Aug 19, 2019 -
KGE Algorithms
ZIP Archive - 19.4 KB -
MD5: d2e8ac74e3f20d2cdec2225962c7e2f0
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Sep 2, 2019
Wiegand, Michael, 2019, "Lexicon of Abusive Words (EN)", https://doi.org/10.11588/data/MKPEYV, heiDATA, V1
This goldstandard contains a bootstrapped lexicon of abusive words. The lexicon comprises a large set of English negative polar expressions annotated as either abusive or not. |
Sep 2, 2019 -
Lexicon of Abusive Words (EN)
ZIP Archive - 738.4 KB -
MD5: 46f33f5b7a9c866b1a2fb6dc956b945d
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Sep 5, 2019 -
Sentiment View Lexicon (EN)
Plain Text - 18.2 KB -
MD5: 4a17ffc27c9f3b240fbf4fe17783c89c
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Sep 5, 2019 -
Sentiment Compound Data (DE)
Plain Text - 18.2 KB -
MD5: 4a17ffc27c9f3b240fbf4fe17783c89c
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Oct 7, 2019 -
Multilingual Modal Sense Classification using a Convolutional Neural Network [Source Code]
ZIP Archive - 3.0 MB -
MD5: 63c05670056bb1992a1e5ec370f0ccf3
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Oct 7, 2019 -
The MSC Data Set
ZIP Archive - 6.2 MB -
MD5: 98dbe1d608c24c3dfd31f166daeee77b
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Oct 7, 2019
Marasović, Ana, 2019, "Multilingual Modal Sense Classification using a Convolutional Neural Network [Source Code]", https://doi.org/10.11588/data/ERDJDI, heiDATA, V1
Abstract Modal sense classification (MSC) is aspecial WSD task that depends on themeaning of the proposition in the modal’s scope. We explore a CNN architecture for classifying modal sense in English and German. We show that CNNs are superior to manually designed feature-based cl... |
Aug 19, 2019
Kotnis, Bhushan, 2019, "Negative Sampling for Learning Knowledge Graph Embeddings", https://doi.org/10.11588/data/YYULL2, heiDATA, V1
Reimplementation of four KG factorization methods and six negative sampling methods. Abstract Knowledge graphs are large, useful, but incomplete knowledge repositories. They encode knowledge through entities and relations which define each other through the connective structure o... |