Microsoft Corporation
Multilevel representation learning for computer content quality

Abstract:

In an example, a piece of content is obtained. The piece of content is segmented into a plurality of segments. Each of the plurality of segments is divided into a plurality of units. Then, for each of the plurality of units for each segment, a quality model is used to pass the unit through a long short-term memory (LSTM) corresponding to the unit, causing an embedding of the unit and generating one or more parameters. For each of the plurality of segments for the piece of content, the quality model is used to pass the segment, and one or more parameters obtained from LSTMs corresponding to units within the segment, through an LSTM corresponding to the segment, causing an embedding of the segment. The piece of content is then classified as spam based on the embeddings of the plurality of segments for the piece of content, using the quality model.