Collaborative topic regression with denoising AutoEncoder for content and community co-representation

Personalized recommendation of items frequently faces scenarios where we have sparse observations on users' adoption of items. In the literature, there are two promising directions. One is to connect sparse items through similarity in content. The other is to connect sparse users through simila...

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Bibliographic Details
Main Authors: NGUYEN, Trong T., LAUW, Hady W.
Format: text
Language:English
Published: Institutional Knowledge at Singapore Management University 2017
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Online Access:https://ink.library.smu.edu.sg/sis_research/3883
https://ink.library.smu.edu.sg/context/sis_research/article/4885/viewcontent/CollaborativeTopicRegression_AutoEncoder_2017.pdf
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Institution: Singapore Management University
Language: English