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Bendersky et al., 2017 - Google Patents

Learning from user interactions in personal search via attribute parameterization

Bendersky et al., 2017

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Document ID
12187557453388967354
Author
Bendersky M
Wang X
Metzler D
Najork M
Publication year
Publication venue
Proceedings of the tenth ACM international conference on web search and data mining

External Links

Snippet

User interaction data (eg, click data) has proven to be a powerful signal for learning-to-rank models in web search. However, such models require observing multiple interactions across many users for the same query-document pair to achieve statistically meaningful gains …
Continue reading at dl.acm.org (PDF) (other versions)

Classifications

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    • G06F17/30—Information retrieval; Database structures therefor; File system structures therefor
    • G06F17/3061—Information retrieval; Database structures therefor; File system structures therefor of unstructured textual data
    • G06F17/30634—Querying
    • G06F17/30657—Query processing
    • G06F17/3066—Query translation
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
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    • G06F17/30—Information retrieval; Database structures therefor; File system structures therefor
    • 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
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    • G06Q10/00—Administration; Management

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