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An emotion tendency detection method for comment data

A technology of emotional tendency and detection method, which is applied in the direction of network data retrieval, other database retrieval, network data indexing, etc., to achieve the effect of improving efficiency

Active Publication Date: 2017-02-15
北京众荟信息技术股份有限公司
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AI Technical Summary

Problems solved by technology

At present, many technologies of natural language processing cannot deal with the variability of language well, so it is a problem that we need to solve further to deal with such complex changes.

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  • An emotion tendency detection method for comment data
  • An emotion tendency detection method for comment data
  • An emotion tendency detection method for comment data

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Embodiment Construction

[0030] In order to make the above objects, features and advantages of the present invention more obvious and understandable, the present invention will be further described below through specific embodiments and accompanying drawings.

[0031] The present invention is an emotional tendency detection method (or emotional tendency analysis method) oriented to review data, which is used for mining user opinions in reviews. The present invention first obtains online review data from major mainstream review websites by focusing crawlers. Then, for large-scale reviews, the semantic dictionary and sentence library are sorted out in a semi-automatic manner. Finally, for each sentence in the review, word segmentation and other processing and analysis are performed, and on this basis, keywords or key sentence patterns are extracted as features, and emotional orientation detection and emotional classification are realized through the maximum entropy classifier. figure 1 It is a flow cha...

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Abstract

The invention relates to an emotion tendency detection method for comment data. The method comprises the steps of 1) acquiring comment data and performing standardization treatment on the same; 2) performing word segmentation treatment on sentences of the comment data subjected to the standardization treatment; 3) performing factor analysis on the sentences subjected to word segmentation and identifying various kinds of words having influence on emotion tendency detection analysis; 4) performing sentence pattern template matching on the comment data subjected to the factor analysis according to a sentence pattern template library; 5) determining antecedents corresponding to reference words in the sentences of the comment data and restoring omitted subjects; 6) regarding sentences containing evaluation object words, evaluation attribute words or emotion words as candidate emotion sentences, and identifying the sentence polarities of the candidate emotion sentences by using the maximum entropy model to obtain the emotion tendencies of the sentences. The method is based on the characteristics of diversification and orality of comment texts and improves the efficiency and the accuracy of comment data emotion tendency detection.

Description

technical field [0001] The invention belongs to the technical fields of information technology and data mining, and in particular relates to an emotional tendency detection method for review data. Background technique [0002] With the rapid development of e-commerce, comments on the Internet have gradually entered people's field of vision, gradually influenced the choices of netizens, and then gradually deepened their influence on brands. Taking the hotel industry as an example, the hotel hopes to use technical means to obtain user comments and feedback, which can be used to guide the hotel's brand management and operation management, and improve the brand image and service quality. Users want to read other people's reviews to clarify the advantages and disadvantages of the hotel, which can be used as an important reference for booking. Tripadvisor research shows that more than 85% of users attach great importance to the quality of hotel reputation, and nearly 90% of users...

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Application Information

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IPC IPC(8): G06F17/30
CPCG06F16/374G06F16/951G06F16/9535
Inventor 林小俊张猛暴筱
Owner 北京众荟信息技术股份有限公司
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