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A Credit Hype and Malicious Evaluation Identification Method Based on Subgraph Mining

A recognition method and sub-graph technology, applied in data processing applications, sales/lease transactions, instruments, etc., can solve problems such as high complexity and poor interpretability, and achieve the effect of promoting fair competition for commodities

Inactive Publication Date: 2022-01-14
SHANGHAI DIANJI UNIV
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Problems solved by technology

Text analysis belongs to the category of natural language processing, and generally requires support vector machine (SVM), deep learning and other models, which have poor interpretability and high complexity

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  • A Credit Hype and Malicious Evaluation Identification Method Based on Subgraph Mining
  • A Credit Hype and Malicious Evaluation Identification Method Based on Subgraph Mining
  • A Credit Hype and Malicious Evaluation Identification Method Based on Subgraph Mining

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Embodiment Construction

[0045] Below in conjunction with specific embodiment, further illustrate the present invention. It should be understood that these examples are only used to illustrate the present invention and are not intended to limit the scope of the present invention. In addition, it should be understood that after reading the teachings of the present invention, those skilled in the art can make various changes or modifications to the present invention, and these equivalent forms also fall within the scope defined by the appended claims of the present application.

[0046] Unreasonable evaluation mainly includes credit hype and malicious evaluation. The main forms of the former include self-purchasing, self-evaluation, entrusted praise and other false positive reviews formed by buyers and sellers under non-"real" transaction conditions; It is a malicious evaluation among peers, or it may be that the evaluator deliberately threatens the merchant, or makes unreasonable demands, such as refu...

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Abstract

The invention provides a method for identifying credit hype and malicious evaluation based on subgraph mining, which is characterized in that it includes the following steps: dividing the evaluation of commodities into favorable and negative evaluations; establishing a semi-secondary network for each commodity; The semi-two-class network is analyzed. Based on online commodity evaluation, the present invention can construct a semi-binary classification network based on specific links between commodities in a massive evaluation data set, and realize the identification of credit speculation and malicious evaluation through network statistical analysis and subgraph mining. This solution has practical significance and application value for standardizing the normal operation of e-commerce platforms, promoting fair competition of commodities, and providing consumers with correct shopping guidelines.

Description

technical field [0001] The present invention is oriented to the evaluation data of online commodities, and aims to identify unreasonable evaluations, including credit hype and malicious evaluations, through semi-secondary network modeling and subgraph mining with multiple connections, so as to standardize the commodity feedback and commodity recommendation market, Promoting the fair and just construction of the Internet environment belongs to the field of network node discovery or pattern recognition. Background technique [0002] At present, there are many papers on the method of identifying credit hype and malicious evaluation. For example: the patent application number is CN201510314327.0, which uses information transmission technology to expand effective credit scores and reduce false evaluations, so that consignor members (for convenience, the following is referred to as consignor member A) can obtain vehicle members that are more suitable for their own needs (for conve...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06Q30/06G06F40/216
CPCG06Q30/0627G06F40/216
Inventor 李建敦
Owner SHANGHAI DIANJI UNIV
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