融合N-Gram的水產(chǎn)養(yǎng)殖長文本實(shí)體關(guān)系聯(lián)合抽取
關(guān)鍵詞:水產(chǎn)養(yǎng)殖;長文本;實(shí)體關(guān)系聯(lián)合抽取;N-Gram算法;多模型融合算法DOI:10. 15938/j. jhust. 2025. 02. 010中圖分類號:TP391.1;S951.2 文獻(xiàn)標(biāo)志碼:A 文章編號:1007-2683(2025)02-0091-13
Abstract:Tosolvetheproblemofmisjudgmentandlossofvalidinformationcausedbyalargeamountof irelevantinformationin aquaculturelongtext,ajointextractionmethodofentityrelationsbasedonN-Gramfusionwasproposed.Firstly,themulti-model fusionalgorithmisused toextract thetextmatrixfeaturemapbasedonBERTiitialization,andthenthecascadingBiLSTMisusedto extractedepfeatures.Afterthat,thefeaturesofthelongtextslcematrixpreprocessedbyfusionN-Gramalgorithmareeracted layerbylayer,andtherelativeandabsolutepositionsofslicematrixaremodeled.Theexperimentalresultsontheself-constructed aquaculturelong textdatasetandSKE publicdataset show significant improvementscompared withthe benchmark model.The experimentalresultsshowthatthismethodcanfullacquireandprocessthesemanticinformation inaquaculturelongtext,and effectively improve the accuracy and integrity of entity relation extraction.
Keywords:aquaculture;long text;joint extractionof entityrelations;N-Gram algorithm;multi-model fusion algorithm
0 引言
隨著我國經(jīng)濟(jì)的高速發(fā)展,各行各業(yè)都在向智慧化方向轉(zhuǎn)型[1-3],水產(chǎn)養(yǎng)殖業(yè)也在向精準(zhǔn)化和集約化的養(yǎng)殖方式轉(zhuǎn)變。(剩余18864字)
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