Statements (30)
| Predicate | Object |
|---|---|
| gptkbp:instanceOf |
gptkb:convolutional_neural_network
|
| gptkbp:advantage |
captures rare word representations
computationally intensive for large vocabularies |
| https://www.w3.org/2000/01/rdf-schema#label |
Skip-gram model
|
| gptkbp:hyperparameter |
learning rate
window size negative sampling embedding dimension |
| gptkbp:implementedIn |
gptkb:Python
gptkb:TensorFlow gptkb:PyTorch |
| gptkbp:input |
target word
|
| gptkbp:introduced |
gptkb:Tomas_Mikolov
|
| gptkbp:introducedIn |
2013
|
| gptkbp:objective |
predict context words given a target word
|
| gptkbp:output |
context words
|
| gptkbp:partOf |
gptkb:Word2Vec
|
| gptkbp:relatedTo |
gptkb:GloVe
gptkb:FastText Continuous Bag of Words model |
| gptkbp:trainer |
large text corpora
|
| gptkbp:usedFor |
information retrieval
text classification analogy tasks semantic similarity word embedding |
| gptkbp:usedIn |
natural language processing
|
| gptkbp:bfsParent |
gptkb:DeepWalk
gptkb:Efficient_Estimation_of_Word_Representations_in_Vector_Space |
| gptkbp:bfsLayer |
7
|