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An automatic classification system and classification method for web comments based on association rules

A technology of opinion classification and rules, applied in the field of semantic processing

Active Publication Date: 2016-12-28
珠海市颢腾智胜科技有限公司
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  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

The reason is that opinion texts on the Web involve the expression of human emotions, and are text content with a very special theme, and their semantic obscurity is higher than that of objective descriptive texts. There are positive words that express irony, and the opposite also exists. These special patterns are difficult to judge by statistical learning methods

Method used

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  • An automatic classification system and classification method for web comments based on association rules
  • An automatic classification system and classification method for web comments based on association rules
  • An automatic classification system and classification method for web comments based on association rules

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Embodiment Construction

[0031] In order to better understand the present invention, some basic concepts are firstly explained.

[0032] Confidence: Confidence reveals whether or not item B will appear when item A appears, or how likely it is to appear. If the degree of confidence is 100%, then A and B can be bundled for sale. If the confidence is too low, it means that the presence of A has little to do with the presence or absence of B.

[0033] Support: Support reveals the probability that item A and item B will appear at the same time. If the probability of A and B appearing at the same time is small, it means that A and B have little relationship; if A and B appear very frequently at the same time, it means that A and B are always related.

[0034]AD-Sup: AD-Sup can be regarded as a mean square error of support. In the above formula, Sup(t) i is the support number of entry t in category i, Sup(FS i ) j Refers to FS i The number of local supports in category j, while Ave(Sup(FS i )) is Sup(...

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Abstract

The invention discloses an association rule-based automatic classification system and classification method for Web comment opinions, which can be divided into four modules: a frequent feature word extraction module, a frequent feature word optimization module, an association rule extraction and mining module, and an opinion classification module. The present invention overcomes the shortcomings of existing systems (such as some systems based on machine learning and emotion classification) that have low precision or require a large amount of human participation or rely too much on natural language processing and professional knowledge. In addition, optimization is carried out in the process of extracting association rule sets, and redundant and indiscriminate association rules are removed, which improves the efficiency of the entire system operation and obtaining results. This system provides an accurate and convenient solution for a variety of situations, such as e-commerce product evaluation, e-government feedback, and Internet user polls.

Description

technical field [0001] The invention relates to an automatic classification system and classification method of Web comments based on association rules, and belongs to the technical field of semantic processing. Background technique [0002] Traditional text opinion classification methods include opinion classification based on machine learning and opinion classification based on sentiment analysis. [0003] Machine learning-based methods use machine learning algorithms in text classification directly for opinion classification, and the accuracy of opinion classification tasks is usually lower than that of text classification tasks for other categories of topics. The reason is that opinion texts on the Web involve the expression of human emotions, and are text content with a very special theme, and their semantic obscurity is higher than that of objective descriptive texts. There are positive words that express irony, and the opposite also exists. These special patterns are...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06F17/30
Inventor 欧阳元新袁满皇甫垚熊璋
Owner 珠海市颢腾智胜科技有限公司
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