基于模糊子空间聚类的个性化旅游推荐模型研究

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中图分类号：TP391.3 文献标识码：A 文章编号：2096-4706（2025）23-0089-08

Abstract： With therapid innovation information technology，thescale data continues to exp thecomplexity continues torise.High-dimensionaldata processngbecomesacore problem that needs tobesolved urgently.Through the combinationsubspace dimensionalityreduction fuzzyclustering，this paper efectively improves the performance tourismrecommendationsystem，ndprovidesnewideasmethodsforsolvingtheproblemigh-dimensionalcomplexdata processing.Theresearchresultsshowthat thescenic spotrecommendation methodcombiningsubspacedimensionalityreduction fuzzyC-meansclustering model showssignificantadvantages indealing withhigh-dimensionalsparse touristdata： subspace dimensionalityreduction technologycan efectively emove data noise，mine potential theme features scenic spots tourists，retaincore informationwhilereducingdatacomplexity.Te fuzzyC-meansclustering modelaccuratelydepicts thediversity tourists'preferencesbyallowingsamples tobelongtomultipleclusterswithdiferentmembershipdegres， the clustering effect is ideal.

Keywords： high-dimensionaldata;subspacedimensionalityreduction;fuzzy C-means clustering;tourismrecommendation model

0 引言

在全球旅游产业蓬勃发展的时代背景下，旅游市场正经历从“大众化”向“个性化”的深刻转型。（剩余11062字）