neural tensor network data

[shuxiaobo]

Hi , Thank for your code, I learned a lot from them, especially NTN, now I wana do some new model and eval on new data set, but I don't know how to generate the embedding mat in the experience of neural tensor network, could you please tell me how to do it? thanks

[GauravBh1010tt]

@shuxiaobo - You may find Convolution neural tensor network as useful. Here, we are passing question-answer vector embeddings to the NTN model that can compute a similarity score for us.
Also, try out DL-text for quick preprocessing and preparing of embeddings.

[shuxiaobo]

I still not find the detail implement, could you tell me what's means of the value in mat_contents described below? 'Word', 'We', and the 'tree', thanks.

\input: Generic function to load embeddings from a .mat file
def load_embeds(file_path):
mat_contents = sio.loadmat(file_path)
words = mat_contents['words']
we = mat_contents['We']
tree = mat_contents['tree']
word_vecs = [[we[j][i] for j in range(embedding_size)] for i in range(len(words[0]))]
entity_words = [map(int, tree[i][0][0][0][0][0]) for i in range(len(tree))]
return (word_vecs, entity_words)