Text topic and emotion joint detection method and device
A joint detection and topic technology, applied in the field of machine learning, can solve the problem of low joint detection accuracy and achieve the effect of improving accuracy
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Embodiment 1
[0022] figure 1 It shows the implementation flow of the text topic and emotion joint detection method provided by the first embodiment of the present invention. For the convenience of explanation, only the parts related to the embodiment of the present invention are shown, and the details are as follows:
[0023] In step S101, the initial sentiment tendency of each word in the input target text is calculated using a preset sentiment dictionary.
[0024] In the embodiment of the present invention, after receiving the text topic and emotion acquisition request sent by the user, the preset emotion dictionary is used to calculate the initial emotion tendency of each word in the input target text. The target text can be a public traditional topic detection data sample, or it can be a data document such as Weibo, blog, forum, and online comment data from the Internet. Of course, after these documents are acquired, preprocessing should be performed on these documents, for example, w...
Embodiment 2
[0040] figure 2 The structure of the text topic and emotion joint detection device provided by Embodiment 2 of the present invention is shown. For the convenience of description, only the parts related to the embodiment of the present invention are shown, including:
[0041] Emotional tendency calculation unit 21, used to calculate the initial emotional tendency of each word in the input target text using a preset sentiment dictionary;
[0042] The word vector setting unit 22 is used to set the word vector of the pre-acquired external corpus as the initial value of the word vector of the target text;
[0043] The text training unit 23 is used to train the input target text using a preset topic-emotion mixed model, so as to obtain the initial distribution between each emotion topic pair and words in the target text; and
[0044] Topic emotion acquisition unit 24, for scanning each document included in the target text according to the initial emotional tendency of each word in...
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