政大機構典藏-National Chengchi University Institutional Repository(NCCUR):Item 140.119/149068

政大機構典藏-National Chengchi University Institutional Repository(NCCUR):Item 140.119/149068

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政大機構典藏 > 商學院 > 資訊管理學系 > 學位論文 > Item 140.119/149068

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題名:	ALBERT空間到直播電商商品空間：一個表示框架 From ALBERT space to livestreaming commerce product space: a representation framework
作者:	謝鴻銘 Hsieh, Hung-Ming
貢獻者:	林怡伶蕭舜文 Lin, Yi-Ling Hsiao, Shun-Wen 謝鴻銘 Hsieh, Hung-Ming
關鍵詞:	直播電商商品表示推薦系統 ALBERT livestreaming commerce product representation recommender system ALBERT
日期:	2023
上傳時間:	2024-01-02 15:38:20 (UTC+8)
摘要:	直播電商市場近年來迅速成長，與傳統電子商務不同，直播電商中的商品並非預先定義的，這樣導致直播店商中的商品尤其複雜。為了幫助消費者在直播電商中找到合適的產品，推薦系統的使用至關重要，而這類系統的效果在很大程度上依賴於強大的商品表示。然而，在直播電商中學習商品表示仍未被充分探索，為此，本研究提出了一個在直播電商中學習商品表示的框架，該框架基於ALBERT將商品名稱轉換為商品表示，用以表示消費者、產品和直播主。此外，我們發現預訓練的語言模型的語料空間不適合用來表示商品，因此我們提出的框架能將語料空間轉換到商品空間，從而提高了推薦效果。最後，我們也嘗試將提出的框架學習到的商品空間進行視覺化，在二維的空間中比較我們的商品表示與語料的商品表示的差異，還有視覺化消費者購買的軌跡及直播主販賣的軌跡。 The livestreaming commerce (LSC) market has experienced rapid growth in recent years. Unlike traditional e-commerce, items in LSC are not predefined, making the items particularly complex. To assist consumers in discovering suitable products in LSC, the use of a recommender system is essential, and the effectiveness of such systems heavily relies on robust product representation. However, learning product representation in LSC remains underexplored. Addressing this gap, this study proposes a framework for learning product representation in LSC. This framework utilizes item names in conjunction with ALBERT to represent consumers, products, and streamers. Furthermore, we find that pre-trained language models' corpus space is inadequate for product representation. Our proposed framework allows the conversion of corpus space into product space, enhancing recommendation performance. Lastly, we visualize the learned product representations, comparing it to the corpus-based product representations in two dimensions. We also visualize consumer purchase trajectories and streamer sales trajectories.
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描述:	碩士國立政治大學資訊管理學系 110356018
資料來源:	http://thesis.lib.nccu.edu.tw/record/#G0110356018
資料類型:	thesis
顯示於類別:	[資訊管理學系] 學位論文

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