Zobrazeno 1 - 7
of 7
pro vyhledávání: '"Xuanwu Liu"'
Publikováno v:
IEEE Transactions on Neural Networks and Learning Systems. 33:304-314
Hashing has been widely adopted for large-scale data retrieval in many domains due to its low storage cost and high retrieval speed. Existing cross-modal hashing methods optimistically assume that the correspondence between training samples across mo
Publikováno v:
IEEE/WIC/ACM International Conference on Web Intelligence.
Autor:
Xuanwu Liu, Donghui Ding, Zehong Hu, Jiajun Bu, Peng Zhang, Chuan Zhou, Haishuai Wang, Zhao Li
Publikováno v:
CIKM
On-demand food delivery (OFD) platforms have greatly impacted the food service industry, where OFD recommendation systems play a central role in enhancing user experience and raising revenues. OFD recommendation, compared with existing online e-comme
Publikováno v:
Database Systems for Advanced Applications ISBN: 9783030594091
DASFAA (1)
DASFAA (1)
Predicting the intention of users for different commodities has been receiving more and more attention in many applications, such as the decision of awarding bonus and the recommendation of commodity in E-commerce. Existing methods treat customer-to-
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::cd4664ac9a41dc7496e64e36c08b185d
https://doi.org/10.1007/978-3-030-59410-7_35
https://doi.org/10.1007/978-3-030-59410-7_35
Publikováno v:
Scopus-Elsevier
AAAI
AAAI
Cross-modal hashing has been receiving increasing interests for its low storage cost and fast query speed in multi-modal data retrievals. However, most existing hashing methods are based on hand-crafted or raw level features of objects, which may not
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5c2b4d180933f669dad0b8a59f0da0d6
http://arxiv.org/abs/1905.04450
http://arxiv.org/abs/1905.04450
Publikováno v:
ICDM
Hashing has been widely studied for big data retrieval due to its low storage cost and fast query speed. Zero-shot hashing (ZSH) aims to learn a hashing model that is trained using only samples from seen categories, but can generalize well to samples
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ff0963078d60246778aee691ea95a8c9
Publikováno v:
IEEE Transactions on Big Data. :1-1
Cross-modal hashing can efficiently retrieve data across different modalities and has been successfully applied in various domains. Although many supervised cross-modal hashing methods have been proposed, they generally focus on two modals only and a