1. A computer automated subject estimation system comprising: a processor; and a memory having a computer program stored thereon, the computer program causing the processor to execute a convolution neural network, wherein the convolution neural network includes: a convolutional layer including one or more topic-dependent convolutional layers and one topic-independent convolutional layer, each of the one or more topic-dependent convolutional layers performing, on an input of a word-string vector sequence corresponding to dialog text transcribed from a dialog, a convolution operation dependent on a topic, and the topic-independent convolutional layer performing, on the input of the word-string vector sequence, a convolution operation not dependent on the topic, a pooling layer performing a pooling process on outputs of the convolutional layer, and a fully connected layer performing a full connection process on outputs of the pooling layer and estimating a subject label of the dialog.
2. The computer automated subject estimation system according to claim 1 , wherein the convolutional neural network estimates the subject label of the dialog with respect to the input by solving the input as a two-class classification problem.