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公开(公告)号：US20250077959A1
公开(公告)日：2025-03-06
申请号：US18461703
申请日：2023-09-06
Applicant: AMPERITY, INC.
Inventor： Yan YAN , Pranav Behari LAL , Nicholas RESNICK , Joyce GORDON
IPC: G06N20/00
Abstract: In some implementations, the techniques described herein relate to a method including: loading a current and a new model, the new model including the most recent version of the current model; computing a migration duration based on computed properties, namely the jitter in predictions between the current and the new models based on imputing the same inference data to both models; blending outputs of the current model with outputs of the new model according to weights computed for a current time step in the migration process; and serving new predictions using the new model when the migration duration expires.
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公开(公告)号：US20240152782A1
公开(公告)日：2024-05-09
申请号：US18390803
申请日：2023-12-20
Applicant: AMPERITY, INC.
Inventor： Yan YAN , Aria HAGHIGHI , Nicholas RESNICK , Andrew LIM
IPC: G06N5/04 , G06F16/23 , G06F16/24 , G06N20/00 , G06Q30/0201
CPC classification number: G06N5/04 , G06F16/2379 , G06F16/24 , G06N20/00 , G06Q30/0201 , G06Q30/0202
Abstract: Disclosed are techniques for generating features to train a predictive model to predict a customer lifetime value or churn rate. In one embodiment, a method is disclosed comprising receiving a record that includes a plurality of fields and selecting a value associated with a selected field in the plurality of fields. The method then queries a lookup table comprising a mapping of values to aggregated statistics using the value and receives an aggregated statistic based on the querying. Next, the method generates a feature vector by annotating the record with the aggregated statistic. The method uses this feature vector as an input to a predictive model.
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公开(公告)号：US20230252503A1
公开(公告)日：2023-08-10
申请号：US17854154
申请日：2022-06-30
Applicant: AMPERITY, INC.
Inventor： Joyce GORDON , Pranav Behari LAL , Nicholas RESNICK , James WU , Yan YAN
CPC classification number: G06Q30/0202 , G06N5/003
Abstract: In some aspects, the techniques described herein relate to a method including: receiving a vector, the vector including a plurality of features related to a user; predicting a return probability for the user based on the vector using a first predictive model; adjusting the return probability using a fitted sigmoid function to generate an adjusted return probability; and predicting a lifetime value of the user using the adjusted return probability and at least one other prediction by combining the adjusted return probability and the at least one other prediction.
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公开(公告)号：US20230128579A1
公开(公告)日：2023-04-27
申请号：US17511747
申请日：2021-10-27
Applicant: AMPERITY, INC.
Inventor： Nicholas RESNICK , Joseph CHRISTIANSON , Joyce GORDON , Andrew LIM , Yan YAN
Abstract: The example embodiments are directed toward predicting the lifetime value of a user using an ensemble model. In an embodiment, a system is disclosed, including a generative model for generating a first prediction representing a first lifetime value of a user during a forecasting period and a discriminative model configured for generating a second prediction representing a second lifetime value of the user during the forecasting period. The system further includes a meta-model for receiving the first prediction and the second prediction and generating a third prediction based on the first prediction and the second prediction, the third prediction representing a third lifetime value of the user during the forecasting period.
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公开(公告)号：US20210263903A1
公开(公告)日：2021-08-26
申请号：US17316293
申请日：2021-05-10
Applicant: AMPERITY, INC.
Inventor： Yan YAN , Stephen Keith MEYLES , Graeme Andrew Kyle ROCHE , Jeffrey Allen STOKES , Carlos Minoru SAKODA , Dan SUCIU
Abstract: The present disclosure relates clustering similar data records together in a hierarchical clustering scheme. Each tier in a cluster corresponds to a minimal match score, which reflects a degree of confidence. In this respect, a higher confidence may lead to smaller sized clusters while a lower confidence may lead to larger sized clusters. Ordinal classification may be used to generate hierarchical clusters. In some embodiments, hierarchical clustering with conflict resolution is used to resolve user-defined hard conflicts in each tier of the clustering results.
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Patent Agency Ranking
公开(公告)号：US20250148322A1
公开(公告)日：2025-05-08
申请号：US19017142
申请日：2025-01-10
Applicant: AMPERITY, INC.
Inventor： Yan YAN , Aria HAGHIGHI , Nicholas RESNICK , Andrew LIM
IPC: G06N5/04 , G06F16/23 , G06F16/24 , G06N20/00 , G06Q30/01 , G06Q30/0201 , G06Q30/0202
Abstract: Disclosed are techniques for generating features to train a predictive model to predict a customer lifetime value or churn rate. In one embodiment, a method is disclosed comprising receiving a record that includes a plurality of fields and selecting a value associated with a selected field in the plurality of fields. The method then queries a lookup table comprising a mapping of values to aggregated statistics using the value and receives an aggregated statistic based on the querying. Next, the method generates a feature vector by annotating the record with the aggregated statistic. The method uses this feature vector as an input to a predictive model.
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公开(公告)号：US20230131884A1
公开(公告)日：2023-04-27
申请号：US17511946
申请日：2021-10-27
Applicant: AMPERITY, INC.
Inventor： Andrew LIM , Joseph CHRISTIANSON , Joyce GORDON , Nicholas RESNICK , Yan YAN
Abstract: The example embodiments are directed toward improvements in generating affinity groups. In an embodiment, a method is disclosed comprising generating probabilities of object interactions for a plurality of users, a given object recommendation ranking for a respective user comprising a ranked list of object attributes; calculating interaction probabilities for each user over a forecasting window; calculating affinity group rankings based on the probabilities of object interactions and the interaction probabilities for each user; and grouping the plurality of users based on the affinity group rankings.
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公开(公告)号：US20210081171A1
公开(公告)日：2021-03-18
申请号：US17104868
申请日：2020-11-25
Applicant: AMPERITY, INC.
Inventor： Stephen MEYLES , Yan YAN , Carlos SAKODA , Ian WESLEY-SMITH , Dan SUCIU
IPC: G06F7/14 , G06F16/2455 , G06F16/215 , G06F16/23 , G06F16/242
Abstract: The present disclosure relates to fuse multiple database tables together. The fields of the database tables may be normalized using semantic fields. Under a first approach, database tables are deduplicated by consolidating redundant records. This may be done by performing pairwise comparisons to identify related pairs of records and then clustering the related pairs of records. Then, the deduplicated database tables are merged by performing another pairwise comparison. Under a second approach, the database tables may be concatenated. Thereafter, records are subject to pairwise comparisons and then clustered to create a merged database table.
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公开(公告)号：US20230273924A1
公开(公告)日：2023-08-31
申请号：US18313753
申请日：2023-05-08
Applicant: AMPERITY, INC.
Inventor： Yan YAN , Aria HAGHIGHI , Joseph CHRISTIANSON
IPC: G06F16/2453 , G06F16/2457 , G06F16/28
CPC classification number: G06F16/24542 , G06F16/24578 , G06F16/285
Abstract: Disclosed are techniques for trimming large clusters of related records. In one embodiment, a method is disclosed comprising receiving a set of clusters, each cluster in the clusters including a plurality of records. The method extracts an oversized cluster in the set of clusters and performs a breadth-first search (BFS) on the oversized cluster to generate a list of visited records. The method terminates the BFS upon determining that the size of the list of visited records exceeds a maximum size and generates a new cluster from the list of visited records and adding the new cluster to the set of clusters. By recursively performing BFS traverse over the oversized cluster and extracting smaller new clusters from it, the oversized cluster is eventually partitioned into a set of sub-clusters with the size smaller than the predefined threshold.
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公开(公告)号：US20230004347A1
公开(公告)日：2023-01-05
申请号：US17930915
申请日：2022-09-09
Applicant: AMPERITY, INC.
Inventor： Derek SLAGER , Stephen MEYLES , Yan YAN , Carlos SAKODA
IPC: G06F7/32 , G06F16/2455
Abstract: The present disclosure relates to merging database tables. Systems and methods may involve performing a comparison between the first set of records and the second set of records and identifying a plurality of record pairs based on the comparison. Each record pair may comprise a record in the first set of records and a record in the second set of records. In addition, A feature signature may be generated for each record pair by comparing field values in each record pair. The feature signature may be classified to identify at least one related record pair. A merged database table may be generated such that it comprises the at least one related record pair and comprises a set of unique records among selected from the first set of records and the second set of records.
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