Personalized commodity recommendation method based on fuzzy object language concept lattice clustering

A language concept, fuzzy object technology, applied in character and pattern recognition, sales/rental transactions, instruments, etc., can solve problems such as information loss, inability to separate object sets, and the inability of hierarchical clustering algorithms to select local optimal levels, etc. Achieve the effect of alleviating the defects of hierarchical clustering and improving interpretability

Pending Publication Date: 2022-07-05
SHANDONG JIANZHU UNIV
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Problems solved by technology

[0005] However, the existing concept lattice clustering algorithm has the problem that the object set cannot be completely divided, and the hierarchical clustering algorithm still has the problem that the local optimal level cannot be selected and the algorithm complexity of applying it to product recommendation is too high
In addition, since the concept lattice still cannot handle the language value information in the personalized product recommendation, it is easy to generate information loss in the information transformation

Method used

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  • Personalized commodity recommendation method based on fuzzy object language concept lattice clustering
  • Personalized commodity recommendation method based on fuzzy object language concept lattice clustering
  • Personalized commodity recommendation method based on fuzzy object language concept lattice clustering

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Embodiment Construction

[0035] Taking commodity recommendation as an example, the personalized commodity recommendation method based on fuzzy object language concept lattice clustering of the present invention is carried out according to the following steps:

[0036] AData collection and preprocessing:

[0037] A1. Set the user's language term set as S={s α |α=-τ,...,-1,0,1,...,τ}, when τ=1, the language term set S={s -1 = bad, s 0 = general, s 1 =good} is used to describe the user's language value preference information for item 1, item 2 and item 3, and use a, b, c to represent item 1, item 2 and item 3 respectively, item set L={a,b,c} , the user set U={X 1 ,X 2 ,X 3 ,X 4 ,X 5 } represents five users;

[0038] A2. Collect User Xp Use language value s α language concepts describing products a, b, c language concept set Initialize user set U and language concept set blurred object language form background As a training set, λ∈[0,1] is the trust level between users and language conce...

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Abstract

The invention discloses a personalized commodity recommendation method based on fuzzy object language concept lattice clustering, and the method comprises the following steps: collecting and processing user behavior data, and initializing the collected data into a fuzzy object language form background; constructing a fuzzy object language concept and a concept lattice; searching a clustering reason; hierarchical clustering is carried out; a hierarchical clustering result corresponds to the reason; obtaining required concepts and hierarchies, and completing clustering; and recommending commodities to the user by adopting Top-N recommendation according to a clustering result. And a concept construction problem can be optimized while a local optimal hierarchy of hierarchical clustering can be found.

Description

technical field [0001] The invention belongs to data mining and intelligent information processing technology, in particular to a personalized commodity recommendation method based on fuzzy object language concept lattice clustering. Background technique [0002] Clustering is to find other similar samples according to the characteristics of the sample itself, so as to achieve the purpose of classifying all samples. Therefore, clustering is often used as a data preprocessing step for other tasks. With the continuous development of Internet technology, e-commerce platforms have gradually become online shopping platforms for people to buy different products. According to the analysis of different users' behavior data, different users' preferences can be determined, which can better provide users with personalized services. [0003] Among all clustering methods, the hierarchical-based clustering method starts with the finest granularity, initializes each sample as a cluster, an...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q30/06G06K9/62
CPCG06Q30/0631G06F18/231
Inventor 邹丽侯铁庞阔路易斯·马丁内斯·洛佩斯
Owner SHANDONG JIANZHU UNIV
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