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Li et al., 2020 - Google Patents

A CTR prediction model based on user interest via attention mechanism

Li et al., 2020

Document ID
10290364247311502480
Author
Li H
Duan H
Zheng Y
Wang Q
Wang Y
Publication year
Publication venue
Applied Intelligence

External Links

Snippet

Recently, click-through rate (CTR) prediction is a challenge problem in the aspect of online advertising. Some researchers have proposed deep learning-based models that follow a similar embedding and MLP paradigm. However, the corresponding approaches generally …
Continue reading at link.springer.com (other versions)

Classifications

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    • G06F17/30861—Retrieval from the Internet, e.g. browsers
    • G06F17/30864—Retrieval from the Internet, e.g. browsers by querying, e.g. search engines or meta-search engines, crawling techniques, push systems
    • G06F17/30867—Retrieval from the Internet, e.g. browsers by querying, e.g. search engines or meta-search engines, crawling techniques, push systems with filtering and personalisation
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
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    • G06Q30/00—Commerce, e.g. shopping or e-commerce
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    • G06Q10/00—Administration; Management
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