Typicality-Based Review Big Data Mining Method

A typical, big data technology, applied in the field of review big data mining based on typicality, can solve the problems of summary, review analysis effect is not ideal, review big data real-time analysis and other problems

Active Publication Date: 2017-11-10
刘耀强
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, in the era of big data, it is almost impossible to manually browse and analyze a large number of online reviews. It is difficult for traditional review mining methods to analyze and summarize the big data of reviews in real time, and the resulting review analysis results are not ideal.

Method used

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  • Typicality-Based Review Big Data Mining Method
  • Typicality-Based Review Big Data Mining Method
  • Typicality-Based Review Big Data Mining Method

Examples

Experimental program
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Effect test

Embodiment

[0080] Such as figure 1 As shown, the typical review big data mining method includes the following steps:

[0081] (1) Modeling of typicality mining of comments, modeling and formal definition of typicality calculation of comments and mining of minimum representative comment sets;

[0082] (2) Automatic construction of typical review prototypes, based on the "basic concept" theory and multi-prototype theory of cognitive psychology to design a typical calculation method for reviews, and use the category utility in the "basic concept" theory to guide the generation of review prototypes;

[0083] (3) Mining the minimum comment set, using the minimum comment set mining algorithm to screen out a minimum comment set, which has the following characteristics: each comment in the set is different and can represent the views of a considerable number of users, the minimum comment set All the comments in can cover and represent the opinions of all the comments of the product. Users only ...

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PUM

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Abstract

The invention discloses a typicality-based big comment data mining method. The method comprises the steps of conducting comment typicality mining modeling, and conducting modeling and formalized definition on comment typicality calculation and the minimum representative comment set mining problem; (2) automatically constructing a typicality comment prototype; (3) conducting minimum comment set mining, and adopting the minimum comment set mining algorithm for screening out one minimum comment set; (4) adopting the BigSimSet parallel computing method, and calling computing nodes in a distributed cluster for processing a similarity comment detection task in a parallel mode. According to the typicality-based big comment data mining method, on the two viewpoints of the cognitive psychology and the viewpoint mining, the user comment typicality balance method is studied, and the minimum comment set with the representativeness is mined on the basis of the method, so that a potential commodity client is helped to know a certain commodity more comprehensively at multiple angles, the user is helped to screen out the needed commodity more accurately, and the user purchase experience is improved.

Description

technical field [0001] The invention relates to the research field of data mining, in particular to a typicality-based comment big data mining method. Background technique [0002] With the rapid development of the Internet of Things in my country, the comments published on e-commerce websites, social networks and various online forums have shown explosive growth. Individual perspectives on a broad range of topics such as consumer products, organisations, people and social events. These product reviews not only allow companies to understand the real needs of customers or potential customers they care about, but also provide useful guidance for consumers' shopping decisions. According to the 2014 China Internet Network Information Center data, more than 90% of online shopping users will post comments under the products on shopping websites. At the same time, more than half of online shoppers said they read reviews of each product before buying it. For example, Ctrip.com pro...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06F17/30
CPCG06F16/9535
Inventor 刘耀强
Owner 刘耀强
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