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Method for evaluating online commodity assessment quality based on Bayesian network

A Bayesian network and quality assessment technology, applied in the field of online commodity evaluation and uncertainty reasoning, which can solve the problems of difficulty in quantifying evaluation quality and inability to give classification confidence of evaluation quality.

Inactive Publication Date: 2017-04-19
KUNMING UNIV OF SCI & TECH
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  • Abstract
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  • Claims
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Problems solved by technology

[0007] The present invention provides an online product evaluation quality evaluation method based on Bayesian network, which is used to solve the problem that the dependence relationship between the evaluation quality and its influencing factors cannot be analyzed from the user's perspective, and the evaluation quality is difficult to quantify and evaluation cannot be given. Quality classification confidence problem, which belongs to the field of online commodity evaluation and uncertainty reasoning

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  • Method for evaluating online commodity assessment quality based on Bayesian network
  • Method for evaluating online commodity assessment quality based on Bayesian network
  • Method for evaluating online commodity assessment quality based on Bayesian network

Examples

Experimental program
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Embodiment 1

[0044] Example 1: Such as Figure 1-2 As shown, a Bayesian network-based online product evaluation quality evaluation method. First, the online product evaluation data is standardized and the online product evaluation quality measurement standard is determined, and the eigenvalue vector is obtained and the eigenvalue matrix is ​​constructed; then according to the characteristics The value matrix is ​​structured to learn to obtain the Bayesian network graph structure, and Bayesian network parameter learning is performed according to the graph structure to obtain the probability parameter table set; finally, the evaluation quality value is probabilistically reasoned, and the maximum probability weight value and corresponding Finally, the evaluation quality metric value is obtained. The evaluation quality metric value of the same product is used to construct the evaluation quality metric value set, and the evaluation data of the same product are sorted according to the evaluation qu...

Embodiment 2

[0049] Example 2: Such as Figure 1-2 As shown, an online product evaluation quality evaluation method based on Bayesian network, this embodiment is the same as embodiment 1, in which:

[0050] The specific steps of Step 1 are:

[0051] Step1.1. Online product evaluation data is the evaluation data of products obtained from e-commerce websites; a product contains multiple evaluation data of different or the same users, and each evaluation data contains text comments, favorable comments, and favorable comments on the product. A set of comprehensive evaluation data such as review or bad review and evaluation time, name, price, etc., where each component is a feature, and text reviews also contain features such as syntax and semantics, using feature function set F=(f 1 (Review i ), f 2 (Review i ),..., f n (Review i )) Review of the original evaluation data of Article i i (i∈Z + ) Perform specific integer set mapping to normalize the original evaluation data; f j (Review i )(1≤j≤n, i∈Z...

Embodiment 3

[0061] Example 3: Such as Figure 1-2 As shown, an online product evaluation quality evaluation method based on Bayesian network, this embodiment is the same as embodiment 2, in which:

[0062] The specific steps of Step 2 are:

[0063] Step2.1. According to the eigenvalue matrix D obtained in Step 1, use the BIC scoring function to judge the merits of the Bayesian graph structure G=(V, S) relative to the eigenvalue matrix D, where V={X 1 ,X 2 ,...,X n } Is a set of evaluation feature nodes, n is the number of feature nodes in G; S is the set of directed edges, which represents the direct dependency between the evaluation features, such as feature node X 1 To X 2 There is an edge, which represents X 2 The value of depends on X 1 , Called X 2 X 1 Child node of X 1 X 2 The parent node of node X, the parent node set of node X is π(X), and the child node set is ch(X); the BIC scoring function is given below:

[0064]

[0065] In the above formula, BIC(G|D) represents the BIC score of G un...

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Abstract

The invention relates to a method for evaluating the online commodity assessment quality based on the Bayesian network, and belongs to the technical field of online commodity assessment and uncertainty reasoning. The method comprises the steps of firstly performing standardization processing on online commodity assessment data, determining an online commodity assessment quality measurement criterion, acquiring an eigenvalue vector and building an eigenvalue matrix; thus acquiring a graph structure of the Bayesian network, and acquiring a probability parameter table set; and finally, performing probabilistic reasoning on an assessment quality value, taking the maximum probability weighted value and a corresponding assessment quality value, finally acquiring an assessment quality measurement value, building an assessment quality measurement value set by assessment quality measurement values of the same commodity, sorting the assessment data of the same commodity according to the assessment quality measurement value, and acquiring an evaluation result. The invention can provide an important assessment quality evaluating method for a third-party platform, and the comment display sequence can be improved in the user perspective, thereby enabling users to check high-quality comment information more conveniently.

Description

Technical field [0001] The invention relates to an online product evaluation quality evaluation method based on a Bayesian network, belonging to the technical field of online product evaluation and uncertainty reasoning. Background technique [0002] With the development of Web2.0, huge changes have taken place in the field of social networking, which has also had a profound impact on the field of e-commerce. J. Roed( <Computer Assisted LanGuaGe LearninG> 16(2–3)(2003)155–172) pointed out that Internet users are willing to disclose their personal information and truly display their views, while J.A. CheValier, D. Mayzlin ( <Journal of MarketinG Research) 43(3)(2006)345-354) also pointed out that user opinions have a great influence on user decision-making, and online product reviews have an indirect verbal marketing effect on products. Therefore, the evaluation information provided by Internet users not only promotes economic exchanges, but also acts as a social forum, a...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/62G06Q10/06
CPCG06Q10/06395G06F18/24155
Inventor 付晓东丁东刘骊刘利军冯勇
Owner KUNMING UNIV OF SCI & TECH
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