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38 lines
1.7 KiB
Scala
38 lines
1.7 KiB
Scala
package com.twitter.follow_recommendations.common.candidate_sources.recent_engagement
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import com.twitter.timelines.configapi.FSBoundedParam
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import com.twitter.timelines.configapi.FSParam
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object RepeatedProfileVisitsParams {
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// If RepeatedProfileVisitsSource is run and there are recommended candidates for the target user, whether or not
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// to actually include such candidates in our output recommendations. This FS will be used to control bucketing of
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// users into control vs treatment buckets.
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case object IncludeCandidates
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extends FSParam[Boolean](name = "repeated_profile_visits_include_candidates", default = false)
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// The threshold at or above which we will consider a profile to have been visited "frequently enough" to recommend
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// the profile to the target user.
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case object RecommendationThreshold
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extends FSBoundedParam[Int](
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name = "repeated_profile_visits_recommendation_threshold",
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default = 3,
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min = 0,
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max = Integer.MAX_VALUE)
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// The threshold at or above which we will consider a profile to have been visited "frequently enough" to recommend
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// the profile to the target user.
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case object BucketingThreshold
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extends FSBoundedParam[Int](
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name = "repeated_profile_visits_bucketing_threshold",
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default = 3,
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min = 0,
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max = Integer.MAX_VALUE)
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// Whether or not to use the online dataset (which has repeated profile visits information updated to within minutes)
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// instead of the offline dataset (updated via offline jobs, which can have delays of hours to days).
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case object UseOnlineDataset
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extends FSParam[Boolean](name = "repeated_profile_visits_use_online_dataset", default = true)
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}
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