TOPIC CLASSIFICATION USING A JOINTLY TRAINED ARTIFICIAL NEURAL NETWORK

In one embodiment, a method includes accessing an input vector representing an input post, wherein the input post includes one or more n-grams and an image, the input vector corresponds to a point in a d-dimensional vector space, the input vector was generated by an artificial neural network (ANN) b...

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Bibliographic Details
Main Authors Zhang, Ying, Yang, Wenhai, Jin, Ou
Format Patent
LanguageEnglish
Published 27.06.2019
Subjects
CALCULATING
COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
COMPUTING
COUNTING
PHYSICS
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Summary:In one embodiment, a method includes accessing an input vector representing an input post, wherein the input post includes one or more n-grams and an image, the input vector corresponds to a point in a d-dimensional vector space, the input vector was generated by an artificial neural network (ANN) based on a text vector representing the one or more n-grams of the input post and an image vector representing the image of the input post; and the ANN was jointly trained to receive a text vector representing one or more n-grams of a post and an image vector representing an image of the post and then output a probability that the received post is related to the training posts of a training page; and determining a topic of the input post based on the input vector.
Bibliography:Application Number: US201715855950