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完整後設資料紀錄
DC 欄位 | 值 | 語言 |
---|---|---|
dc.contributor.advisor | 鄭卜壬 | zh_TW |
dc.contributor.advisor | Pu-Jen Cheng | en |
dc.contributor.author | 蔡易儒 | zh_TW |
dc.contributor.author | Yi-Ru Tsai | en |
dc.date.accessioned | 2023-12-20T16:29:13Z | - |
dc.date.available | 2023-12-21 | - |
dc.date.copyright | 2023-12-20 | - |
dc.date.issued | 2023 | - |
dc.date.submitted | 2023-11-30 | - |
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dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/91322 | - |
dc.description.abstract | 這篇論文的重點是解決推薦系統中學習內容一致性的挑戰。我們提出了一種新穎的模型,旨在學習跨模態和跨項目的表示,有效捕捉相似項目內容的文本和視覺語義。我們在這項研究中將嵌入應用於推薦系統和主題生成。廣泛實驗在三個真實的亞馬遜數據集上的結果表明,與現有的知名模型相比,在這兩個應用中都取得了顯著的改善。 | zh_TW |
dc.description.abstract | The paper focuses on tackling the challenge of learning content consistency in recommender systems. We introduce a novel model that aims to learn cross-modal and cross-item representations, effectively capturing the textual and visual semantics of similar item contents. We apply the embedding to the recommender system and topic generation in this research. The results of extensive experiments on three real Amazon datasets show significant improvement in both applications, compared to existing well-known models. | en |
dc.description.provenance | Submitted by admin ntu (admin@lib.ntu.edu.tw) on 2023-12-20T16:29:13Z No. of bitstreams: 0 | en |
dc.description.provenance | Made available in DSpace on 2023-12-20T16:29:13Z (GMT). No. of bitstreams: 0 | en |
dc.description.tableofcontents | Verification Letter from the Oral Examination Committee i
Acknowledgements ii 摘要 iii Abstract iv Contents v List of Figures vii List of Tables ix Denotation xi Chapter 1 Introduction 1 Chapter 2 Related Works 7 2.1 Recommendation . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 2.1.1 Content-Based Models . . . . . . . . . . . . . . . . . . . . . . . . 7 2.1.2 Collaborative Filtering . . . . . . . . . . . . . . . . . . . . . . . . 8 2.1.3 Hybrid Methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9 2.2 Topic Generation . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10 2.2.1 Text Semantics . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10 2.2.2 Vision Semantics . . . . . . . . . . . . . . . . . . . . . . . . . . . 11 2.2.3 Vision-language Representation Learning . . . . . . . . . . . . . . 12 Chapter 3 Methodology 14 3.1 Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14 3.1.1 Problem Formulation . . . . . . . . . . . . . . . . . . . . . . . . . 14 3.2 Aligned Cross-Modal and Cross-Item Encoder . . . . . . . . . . . . 15 3.2.1 Aligned Cross-Modal Encoder . . . . . . . . . . . . . . . . . . . . 15 3.2.1.1 Image-Text Contrastive Loss (ITC) . . . . . . . . . . . 15 3.2.1.2 Masked Language Modeling Loss (MLM) . . . . . . . 16 3.2.1.3 Image-Text Matching Loss (ITM) . . . . . . . . . . . . 16 3.2.2 Aligned Cross-Item Encoder . . . . . . . . . . . . . . . . . . . . . 17 3.2.2.1 Item-Item Contrastive Loss (IIC) . . . . . . . . . . . . 17 3.2.2.2 Item-Item Matching Loss (IIM) . . . . . . . . . . . . . 17 3.3 Embedding Propagation Model . . . . . . . . . . . . . . . . . . . . 18 3.4 Consistent Content Decoder . . . . . . . . . . . . . . . . . . . . . . 19 3.5 Recommender System . . . . . . . . . . . . . . . . . . . . . . . . . 20 3.6 Bayesian Personalized Ranking Bonus Loss . . . . . . . . . . . . . . 20 Chapter 4 Experiments 24 4.1 Dataset and Experimental Settings . . . . . . . . . . . . . . . . . . . 24 4.2 Experimental Results and Discussion . . . . . . . . . . . . . . . . . 25 4.2.1 Recommendation . . . . . . . . . . . . . . . . . . . . . . . . . . . 25 4.2.2 Consistent Content Topic Generation . . . . . . . . . . . . . . . . . 28 4.3 Ablation Study . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32 Chapter 5 Conclusions 36 References 37 | - |
dc.language.iso | en | - |
dc.title | 保持內容一致性的學習方法:跨模態和跨項目的表示學習 | zh_TW |
dc.title | YR-REC: Yoked and Refined Representation with Content Consistency for Recommendation and Explanation | en |
dc.type | Thesis | - |
dc.date.schoolyear | 112-1 | - |
dc.description.degree | 碩士 | - |
dc.contributor.oralexamcommittee | 曾新穆;高宏宇;江俊宇;黃瀚萱 | zh_TW |
dc.contributor.oralexamcommittee | Shin-Mu Tseng;Hung-Yu Kao;Jyun-Yu Jiang;Hen-Hsen Huang | en |
dc.subject.keyword | 交叉注意,跨模態,跨項目,主題生成, | zh_TW |
dc.subject.keyword | cross-attention,cross-modal,cross-item,topic generation, | en |
dc.relation.page | 44 | - |
dc.identifier.doi | 10.6342/NTU202301098 | - |
dc.rights.note | 未授權 | - |
dc.date.accepted | 2023-12-01 | - |
dc.contributor.author-college | 電機資訊學院 | - |
dc.contributor.author-dept | 資訊網路與多媒體研究所 | - |
顯示於系所單位: | 資訊網路與多媒體研究所 |
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