Using feedback to create and modify candidate streams
Techniques for dynamically altering weights to re-weight attributes of an ordering model based on feedback in a streaming environment are described. In an embodiment, a system accesses, based on a candidate stream definition comprising a role including a title, one or more stream-related information...
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Zusammenfassung: | Techniques for dynamically altering weights to re-weight attributes of an ordering model based on feedback in a streaming environment are described. In an embodiment, a system accesses, based on a candidate stream definition comprising a role including a title, one or more stream-related information sources, and extracts attributes from the sources. Additionally, the system inputs the attributes to a combined ordering model that is trained by a machine learning algorithm to output ordering scores for member profiles of an online system (e.g., hosting a social networking service). The combined ordering model includes weights assigned to the attributes. Moreover, the system orders, based on the ordering scores, the profiles. Furthermore, the system presents, on a display, of top-ordered profiles. Then, the system accesses feedback regarding the top-ordered profiles and dynamically trains the weights assigned to each of the attributes to alter the weights assigned to the attributes based on the feedback. |
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