DSSM

Reference:

PS Huang et al. “Learning Deep Structured Semantic Models for Web Search using Clickthrough Data” in CIKM 2013.

class recbole.model.context_aware_recommender.dssm.DSSM(config, dataset)

Bases: ContextRecommender

DSSM respectively expresses user and item as low dimensional vectors with mlp layers, and uses cosine distance to calculate the distance between the two semantic vectors.

calculate_loss(interaction)

Calculate the training loss for a batch data.

Parameters:

interaction (Interaction) – Interaction class of the batch.

Returns:

Training loss, shape: []

Return type:

torch.Tensor

forward(interaction)

Defines the computation performed at every call.

Should be overridden by all subclasses.

Note

Although the recipe for forward pass needs to be defined within this function, one should call the Module instance afterwards instead of this since the former takes care of running the registered hooks while the latter silently ignores them.

predict(interaction)

Predict the scores between users and items.

Parameters:

interaction (Interaction) – Interaction class of the batch.

Returns:

Predicted scores for given users and items, shape: [batch_size]

Return type:

torch.Tensor

training: bool