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Personalized recommendation method based on fuzzy object language concept lattices

A language concept, fuzzy object technology, applied in special data processing applications, instruments, electrical digital data processing, etc., can solve problems such as cold start, inability to process language information, and vague recommendation interpretation

Active Publication Date: 2020-08-28
LIAONING NORMAL UNIVERSITY
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AI Technical Summary

Problems solved by technology

[0006] However, the existing association rule extraction algorithms based on concept lattices applied to recommendation systems still have the problems of fuzzy recommendation interpretation and cold start. In addition, because concept lattices still cannot handle language information, it is easy to cause information loss.

Method used

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  • Personalized recommendation method based on fuzzy object language concept lattices
  • Personalized recommendation method based on fuzzy object language concept lattices
  • Personalized recommendation method based on fuzzy object language concept lattices

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Embodiment Construction

[0044] Taking teaching resources as supplies, the personalized recommendation method based on fuzzy object language concept lattice of the present invention is as follows: Figure 5 As shown, follow the steps below:

[0045] AData collection and preprocessing:

[0046] A1. Set language term set as S={s α |α=-τ,...,-1,0,1,...,τ}, when τ=1, language term set S={s -1 = not good, s 0 = General, s 1 =good} means describing the language value of each type of teaching resources, respectively using l 1 , l 2 , l 3 Represents three types of teaching resources, item set L={l 1 , l 2 , l 3}, user set U={x 1 ,x 2 ,x 3 ,x 4} means four users;

[0047] A2. Collect user x r Use language value s α Describe the item l i language concept set of language concepts Initialize user set U and language concept set Fuzzy object language form background As a training set, λ∈[0,1] is the level of trust between the user and the language concept, the threshold T=0.5, For user se...

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Abstract

The invention discloses a personalized recommendation method based on a fuzzy object language concept lattice, which can solve the problems of fuzzy recommendation interpretation and cold start and avoid information loss, and comprises the following steps: data processing: initializing a collected training data set into a fuzzy object language form background; constructing fuzzy object language concepts and concept lattices; calculating evaluation differences between the to-be-recommended user and other users; performing preliminary processing on the training data set according to the evaluation difference; constructing a cognitive system of the training data set; constructing a sufficient knowledge base and a fuzzy object language knowledge simulation lattice of the training data set; constructing a necessary knowledge base and a fuzzy object language knowledge simulation lattice of the training data set; calculating a frequent fuzzy object language concept or frequent fuzzy object language knowledge; calculating a fuzzy object language association rule; and calculating a recommendation rule base and carrying out recommendation.

Description

technical field [0001] The invention belongs to data mining and intelligent information processing technology, in particular to a personalized recommendation method based on fuzzy object language concept lattice, which can solve the problem of fuzzy recommendation explanation and cold start, and can avoid information loss. Background technique [0002] Formal concept analysis (FCA) is a method proposed by Wille in 1982 to analyze the conceptual hierarchy based on the formal background. Concepts are described by extension and connotation satisfying certain closure properties, and all concepts generated in the formal background constitute a complete concept lattice, which is used to describe the hierarchical structure relationship of formal concepts and analyze the generalization and specialization relationship between concepts. [0003] Representing qualitative concepts with linguistic values ​​is the basis of human thinking, which is both random and fuzzy. Zadeh introduced ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F16/2457
CPCG06F16/2457Y02D10/00
Inventor 刘新庞阔邹丽
Owner LIAONING NORMAL UNIVERSITY
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