Training method of film review emotional orientation analysis based on machine learning
A kind of emotional tendency and machine learning technology, applied in the direction of instruments, computer parts, computing, etc., can solve the problem of low accuracy of emotional overall tendency judgment, and achieve the effect of accurate overall tendency and accurate judgment
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Embodiment 1
[0045] This embodiment is aimed at the emotional tendency analysis of Chinese film reviews, and it proposes a method for discriminating emotional tendency, mainly including training methods, testing methods, and analysis methods. The program uses machine learning to extract feature words and convert text into features The representation form and the classifier are constructed by naive Bayesian thinking, and the feature extraction adopts part-of-speech selection to avoid not extracting meaningful features due to the lack of movie reviews.
[0046] The technical scheme disclosed in this embodiment is as follows:
[0047] A method for analyzing the emotional tendency of film reviews based on machine learning, comprising the following steps:
[0048] Step 1: Write a crawler to download Douban movie reviews, and the downloaded movie reviews form a corpus;
[0049] Step (a): Get the URL of the movie to be downloaded in Douban.
[0050] Step (b): Download the movie review, movie name...
Embodiment 2
[0115] As an example supplement to the technical solution in Example 1, figure 1 The process flow of the analysis method of the present invention is shown. In this embodiment, jieba word segmentation is used to segment a large number of texts and select specific part-of-speech words, and use jieba word segmentation to extract the stem word of the sentence, take the union of the two, and evaluate the downloaded movie reviews according to their ratings. Classification, including positive and negative categories. And convert the movie review text into the form of feature representation, use the classification algorithm to build a classifier, and then perform necessary post-processing. Let's take a movie review in the data set as an example, combined with figure 1 The present invention will be described in detail.
[0116] Step 1. Download movie reviews, write a crawler to download movie reviews from Douban Movies. For example, one of the movie reviews downloaded is as follows:...
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