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  4. Active Learning Based Clothing Image Recommendation with Implicit User Preferences
 
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Active Learning Based Clothing Image Recommendation with Implicit User Preferences

Journal
IEEE International Conference on Multimedia & Expo (ICME)
Date Issued
2013
Author(s)
C.-M. Huang
C.-P. Wei
Y.-C. F. Wang
YU-CHIANG WANG  
王鈺強
DOI
10.1109/icmew.2013.6618318
URI
https://scholars.lib.ntu.edu.tw/handle/123456789/427517
Abstract
We address the problem of user-specific clothing image recommendation in this paper. Different from prior retrieval approaches, we advance an active learning scheme during retrieval for inferring user preferences. With a recently developed sparse-coding based algorithm for content-based image retrieval, we utilize support vector regression (SVR) with a user-interaction training stage to observe user preferences based on the feedback of retrieval results. Therefore, there is no need to explicitly ask his/her preferences such as desirable colors or patterns of clothing images. A subjective evaluation on a commercial clothing image dataset confirms the effectiveness of our method, which is shown to produce more satisfactory recommendation results when comparing to state-of-the-art content-based image retrieval approaches.
Type
conference paper

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