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非常感谢您分享的代码。 在skip-gram,我有些问题请教下您, I_z = {center: 1}这个地方是不是应该是计算context的节点吧, V = np.array(node_list[contexts]['embedding_vectors']) 应该是计算center的节点embedding吧, 最终更新的是 for z in context_u: tmp_z, tmp_loss = skip_gram(u, z, neg_u, node_list_u, lam, alpha) node_list_u[z]['embedding_vectors'] += tmp_z ## 这里是不是更新center节点的embedding吧?
十分期待您的解答!
The text was updated successfully, but these errors were encountered:
我觉得是I_z = {contexts: 1},V = np.array(node_list[center]['embedding_vectors'])。这样才和论文的公式一致
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是的!我觉得也是
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非常感谢您分享的代码。
在skip-gram,我有些问题请教下您,
I_z = {center: 1}这个地方是不是应该是计算context的节点吧,
V = np.array(node_list[contexts]['embedding_vectors']) 应该是计算center的节点embedding吧,
最终更新的是
for z in context_u:
tmp_z, tmp_loss = skip_gram(u, z, neg_u, node_list_u, lam, alpha)
node_list_u[z]['embedding_vectors'] += tmp_z ## 这里是不是更新center节点的embedding吧?
十分期待您的解答!
The text was updated successfully, but these errors were encountered: