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研究生:張宇涵
研究生(外文):Chang, Yu-Han
論文名稱:使用深度特徵融合方法結合圖像與文本資訊於假新聞檢測之研究
論文名稱(外文):The Research on Fake News Detection Using Deep Feature Fusion Method Combining Image and Text Information Analysis
指導教授:林斯寅林斯寅引用關係
指導教授(外文):Lin, Szu-Yin
口試委員:李鍾斌柯志坤李昕潔夏至賢
口試委員(外文):LI, JUNG-BINKe, Chih-KunHsiao, Wei-HsinHSIA, CHIH-HSIEN
口試日期:2022-07-20
學位類別:碩士
校院名稱:國立宜蘭大學
系所名稱:資訊工程學系碩士班
學門:工程學門
學類:電資工程學類
論文種類:學術論文
論文出版年:2022
畢業學年度:110
語文別:中文
論文頁數:64
中文關鍵詞:假新聞深度學習機器學習多模態融合自然語言處理BERT
外文關鍵詞:Fake NewsDeep LearningMachine LearningMultimodal FusionNLPBERT
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  • 被引用被引用:0
  • 點閱點閱:151
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  • 下載下載:0
  • 收藏至我的研究室書目清單書目收藏:0
摘要........................................................................................................................I
Abstract ................................................................................................................ II
誌謝.....................................................................................................................III
目錄.....................................................................................................................IV
表目錄.................................................................................................................VI
圖目錄.............................................................................................................. VIII
第一章 緒論......................................................................................................... 1
1.1 研究背景................................................................................................. 1
1.2 研究動機................................................................................................. 2
1.3 研究問題與目的..................................................................................... 3
1.4 每章節介紹............................................................................................. 3
第二章 文獻探討................................................................................................. 5
2.1 假新聞(Fake News)........................................................................... 5
2.2 自然語言處理......................................................................................... 5
2.2.1 Word2vec ..................................................................................... 6
2.2.2 BERT............................................................................................ 7
2.3 多模態融合 (Multimodal Fusion).................................................... 9
2.3.1 Fusion Strategies.......................................................................... 9
2.4 ResNet50 ............................................................................................... 10
2.5 過去相關研究....................................................................................... 11
第三章 研究方法與設計................................................................................... 13
3.1 研究架構............................................................................................... 13
3.2 使用資料集........................................................................................... 14
3.3 資料前處理........................................................................................... 18
3.5 特徵擷取............................................................................................... 20
3.6 融合方法............................................................................................... 23
3.7 分類模型.............................................................................................. 26
V
3.8 評估指標............................................................................................... 27
第四章 實驗設計與結果................................................................................... 30
4.1 實驗環境............................................................................................... 30
4.2 實驗設計............................................................................................... 31
4.2.1 實驗一:單一特徵對於假新聞辨識模型的效益比較 ........... 31
4.2.2 實驗二:資料平衡方法預測表現比較.................................... 31
4.2.3 實驗三:假新聞使用融合特徵中 Early Fusion 方法的比較. 31
4.2.4 實驗四:假新聞使用融合特徵中 Joint Fusion 方法的比較.. 31
4.2.5 實驗五:假新聞使用融合特徵中 Late Fusion 方法的比較 .. 32
4.2.6 實驗六:探討與過往論文比較結果差異................................ 32
4.3 實驗結果............................................................................................... 32
4.3.1 實驗一:每種特徵資訊分類建模及辨識................................ 33
4.3.2 實驗二:使用資料平衡比對.................................................... 37
4.3.3 實驗三:將每種資訊以 Early Fusion 方式融合分類及預測. 42
4.2.4 實驗四:將每種資訊以 Joint Fusion 方式融合分類及預測.. 45
4.3.5 實驗五:將每種資訊以 Late Fusion 方式融合分類及預測 .. 46
4.3.6 實驗六:對比其他論文之結果................................................ 50
4.4 實驗統整結果....................................................................................... 52
4.5 實驗時間成本....................................................................................... 54
第五章 結論....................................................................................................... 56
5.1 研究結果............................................................................................... 56
5.2 論文貢獻............................................................................................... 57
5.3 研究限制與未來研究建議................................................................... 57
參考文獻............................................................................................................. 59

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