Zero-Shot Heterogeneous Transfer Learning from Recommender Systems to Cold-Start Search Retrieval

Tao Wu
Tao Wu
Ellie Ka-In Chio
Ellie Ka-In Chio
Yu Du
Yu Du
Dima Kuzmin
Dima Kuzmin
Ritesh Agarwal
Ritesh Agarwal
Li Zhang
Li Zhang
John Anderson
John Anderson
Sarvjeet Singh
Sarvjeet Singh

CIKM '20: The 29th ACM International Conference on Information and Knowledge Management Virtual Event Ireland October, 2020, pp. 2821-2828, 2020.

被引用0|引用|浏览54|DOI:https://doi.org/10.1145/3340531.3412752
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其它链接arxiv.org|dl.acm.org|dblp.uni-trier.de|academic.microsoft.com

摘要

Many recent advances in neural information retrieval models, which predict top-K items given a query, learn directly from a large training set of (query, item) pairs. However, they are often insufficient when there are many previously unseen (query, item) combinations, often referred to as the cold start problem. Furthermore, the search s...更多

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