基于深度學(xué)習(xí)的網(wǎng)頁內(nèi)容解析方法

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中圖分類號：TP391；TP301.6；TP311.1 文獻(xiàn)標(biāo)識碼：A 文章編號：2096-4706（2025）08-0106-06

Abstract： Inorder to extract valuable information from Web pages eficientlyand accurately，this paper proposes a Web content parsing methodbasedonDeep Learning.This methodaims to extracttext information fromcomplex HyperText MarkupLanguage（HTML）.This methodcombines the feature extractionabilityofDeepLeaming，NaturalLanguageProcessing technologyandlayoutinformationinHMLdocumentstoconstructaMulti-LayerNeuralNetworkmodel，soastoealizete recognitionof Webcontent.The experimentalresultsshowthatcompared withthe traditional Webcontentextraction method based on text density， this method has obvious advantages in accuracy，adaptability and robustness.

Keywords：Web content parsing;DeepLearning; Neural Network; adaptability

0 引言

隨著互聯(lián)網(wǎng)的發(fā)展，網(wǎng)頁的功能、樣式結(jié)構(gòu)變得越來越復(fù)雜。（剩余6748字）