Classification method and system of emotions of news readers
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A news and emotion technology, applied in the field of information classification, can solve the problems of time-consuming and labor-intensive, and it is difficult to improve the performance of news readers' emotion classification
Inactive Publication Date: 2015-12-30
ZHANGJIAGANG INST OF IND TECH SOOCHOW UNIV
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[0004] Most of the previous research work is based on fully supervised learning methods. The premise of fully supervised learning methods is that there is a sufficiently large-scale labeled corpus.
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Embodiment 1
[0036] This embodiment provides a classification method of news reader sentiment, figure 1 The flowchart of this embodiment is shown, including:
[0037] Step S101: Obtain news text and comment text from the target corpus, obtain the word feature information of the news text and the comment text, and merge the word feature information of the news text and the comment text;
[0038] Get the news text and the comment text, and the news text and the comment text correspond one by one. When obtaining the word feature information of news text and comment text, since there is no obvious word segmentation information between words in the sentence, the text needs to be segmented, and the ICTCLAS word segmentation tool can be used to segment it. When fusing the word feature information of the news text and the comment text, in order to distinguish the news text feature and the comment text feature in the fusion feature, a preset symbol can be used to add one of the types of features, such a...
Embodiment 2
[0063] This embodiment provides a classification system of news reader sentiment, image 3 Shows a schematic structural diagram of this embodiment, including:
[0064] Word feature information fusion module 101, corpus format conversion module 102, corpus classification module 103, sample update module 104, and annotation verification module 105;
[0065] The word feature information fusion module 101 is used to obtain news text and comment text from a target corpus, and obtain the word feature information of the news text and the comment text, and combine the information of the news text and the comment text Word feature information is fused;
[0066] The corpus format conversion module 102 is used to convert the fused word feature information into usable corpus in a format corresponding to the maximum entropy model;
[0067] The corpus classification module 103 is configured to divide the available corpus into training corpus and test corpus according to preset rules, and divide the...
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Abstract
The invention discloses a classification method and system of emotions of news readers. The classification method comprises the following steps: acquiring a news text and a comment text as well as word characteristic information from target linguistic data; fusing the word characteristic information and converting the word characteristic information into available linguistic data with a corresponding format of a maximum entropy model; dividing the available linguistic data into training linguistic data and testing linguistic data according to a pre-set rule, and dividing the training linguistic data into marked samples and unmarked samples; training the marked samples to obtain a maximum entropy model; classifying emotion classes of the unmarked samples by using the maximum entropy model to obtain posterior probability of each emotion class corresponding to the unmarked sample; carrying out emotion class marking on the unmarked samples with the preset quantity and maximum uncertainty of the posterior probability to form new marked samples, and updating the current marked samples and unmarked samples; and circulating the last step until all the unmarked samples are marked. The classification method and system can be used for efficiently classifying the emotions of the news readers when the scale of marking the linguistic data is relatively small.
Description
Technical field [0001] The present invention relates to the field of information classification, in particular to a method and system for classifying news reader emotions. Background technique [0002] The rapid development of Web technology has promoted the continuous transformation of the Internet to an "interactive Internet", and has gradually become an important carrier of various information in society. With the rise of various social platforms, more and more user-generated content on the Internet has produced a large amount of text information, such as news, microblogs, and blogs. Faced with such large and emotionally expressed text information, it is entirely possible to consider serving people by exploring their potential value. In order to process and analyze these information resources, sentiment analysis has become a basic hot research task in the field of computational linguistics. Here, emotions specifically refer to subjective psychological feelings and objective ...
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