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Short text opinion excavation method based on complementation corpus

A technology of opinion mining and short text, applied in the field of short text opinion mining and short text opinion mining based on complementary corpus, it can solve the problems of unrealistic, noisy data, short length, etc., and achieve the effect of overcoming blurred theme

Active Publication Date: 2016-12-14
NAT COMP NETWORK & INFORMATION SECURITY MANAGEMENT CENT
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Problems solved by technology

[0003] However, these review texts are typical short texts, which have the characteristics of short length and lots of noise data. At the same time, the workload of manual analysis and induction of short texts is heavy, which is almost unrealistic. Therefore, combined with natural language processing, machine learning and other technologies to analyze the Opinion mining of short texts has once become a research hotspot and difficulty in academics and industry

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  • Short text opinion excavation method based on complementation corpus
  • Short text opinion excavation method based on complementation corpus
  • Short text opinion excavation method based on complementation corpus

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Embodiment Construction

[0058] The present invention will be further described in detail below in conjunction with the accompanying drawings.

[0059] The present invention further considers the disadvantages of short texts in attribute-based opinion mining, that is, short texts are more emotional and colloquial, so that the theme or attributes are relatively vague. On the contrary, the attributes of news texts are prominent, but the opinions are relatively monotonous and obscure. . In view of this, the present invention introduces a short text opinion mining method based on complementary corpus, combines news text mining event topics hidden in microblog short texts, and compares and analyzes opinions in microblogs and news under each topic, Finally, analyze the polarity of the point of view.

[0060] First, the maximum entropy model is trained in the short text corpus, and an automatic classifier for attribute words (objective words) and opinion words (subjective words) is established to simultaneo...

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Abstract

The invention discloses a short text opinion excavation method based on complementation corpus, and belongs to attribute opinion excavation; the method comprises the following steps: firstly selecting training corpus from certain segment of weibo corpus, segmenting words, tagging part-of-speech, and selecting; tagging attribute words for training corpus according to opinion words; using part of speech tags as a characteristic training maximum entropy model; then, building a cross-corpus topic model according to weibo corpus and news corpus of certain event, combining the maximum entropy model to parse the topic to which the event belongs, and extracting corresponding attribute word distribution and opinion word distribution; finally, using an emotion classifier to carry out polarity analysis according to all opinion words of certain specific sharing topic or all opinion words of certain specific exclusive topic. The short text opinion excavation method can carry out attribute analysis and opinion excavation on certain public opinion event, has high effectiveness, robustness and usability, and can provide important application values on opinion excavation and public opinion monitoring fields.

Description

technical field [0001] The invention belongs to the field of data mining, and relates to a short text viewpoint mining technology, in particular to a short text viewpoint mining method based on complementary corpus. Background technique [0002] With the rapid development of Web 2.0 technology, Internet users generate a large amount of content, especially in the field of e-commerce, a large number of user-generated product experience and comments have been generated. These product reviews have an important impact on the formation of product reputation. Comments provide a rich source of data for online social opinion analysis. [0003] However, these review texts are typical short texts, which have the characteristics of short length and lots of noise data. At the same time, the workload of manual analysis and induction of short texts is heavy, which is almost unrealistic. Therefore, combined with natural language processing, machine learning and other technologies to analyze...

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Application Information

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IPC IPC(8): G06F17/30G06F17/27
CPCG06F16/951G06F40/289
Inventor 何跃鹰吴俊杰赵忠华董建武徐剑林浩左源
Owner NAT COMP NETWORK & INFORMATION SECURITY MANAGEMENT CENT
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