I'm trying to build a model with text embeddings from books as one input parameter along with reading history.
I have done text analysis to get fixed sized embeddings representing each books content. I have a 1x150 dimensional vector with the text embeddings. Is it correct to build the item feature data that is feeded into the dataset.build_item_features on the following format: [item_id:{feature0:embeddingvector[0],feature1:embeddingvector[1]} .. etc]?
Hi!
I'm trying to build a model with text embeddings from books as one input parameter along with reading history.
I have done text analysis to get fixed sized embeddings representing each books content. I have a 1x150 dimensional vector with the text embeddings. Is it correct to build the item feature data that is feeded into the dataset.build_item_features on the following format: [item_id:{feature0:embeddingvector[0],feature1:embeddingvector[1]} .. etc]?
Like this example:
Thanks, Robin