Factored model for search results and communications based on search results

In an example embodiment, two machine learned models are trained. One is trained to output a probability that a searcher having a member profile in a social networking service will select a potential search result. The other is trained to output a probability that a member corresponding to a potenti...

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Bibliographische Detailangaben
Hauptverfasser: Wu, Xianren, Guo, Qi, Hu, Bo, Nair, Anish Ramdas, Zhou, Shan, Cottle, III, Lester Gilbert
Format: Patent
Sprache:eng
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Beschreibung
Zusammenfassung:In an example embodiment, two machine learned models are trained. One is trained to output a probability that a searcher having a member profile in a social networking service will select a potential search result. The other is trained to output a probability that a member corresponding to a potential search result will respond to a communication from a searcher. Features may be extracted from a query, information about the searcher, and information about the member corresponding to the potential search result and fed to the machine learned models. The outputs of the machine learned models can be combined and used to rank search results for returning to the searcher.