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公开(公告)号：US10268749B1
公开(公告)日：2019-04-23
申请号：US14990161
申请日：2016-01-07
Applicant: Amazon Technologies, Inc.
Inventor： Gourav Roy , Amit Chandak , Prateek Gupta , Srujana Merugu , Aswin Natarajan , Sathish Kumar Palanisamy , Gowda Dayananda Anjaneyapura Range , Jagannathan Srinivasan , Bharath Venkatesh
Abstract: An approximate data structure to represent clusters of observation records of a data set is identified. A hierarchical representation of a plurality of clusters, including the targeted number of clusters among which the observation records are to be distributed, is generated. Each node of the hierarchy comprises an instance of the approximate data structure. Until a set of termination criteria are met, iterations of a selected clustering methodology are run. In a given iteration, distances of observation records from the cluster representatives of a current version of the model are computed using the hierarchical representation, and a new version of the model with modified cluster representatives is generated.
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公开(公告)号：US10089675B1
公开(公告)日：2018-10-02
申请号：US14918445
申请日：2015-10-20
Applicant: Amazon Technologies, Inc.
Inventor： Rajeev Ramnarain Rastogi , Varnit Agnihotri , Rushi Bhatt , Srujana Merugu
Abstract: Data mining systems and methods are disclosed for associating users with items based on underlying personas. The system associates each user account with one or more underlying personas that contribute to the user's interactions with different items, and models user-to-item associations in accordance with the underlying personas based on probabilistic matrix factorization. The system may further predict an active persona for a user based on the user's recent interactions with items and make item related recommendations that are oriented to the active persona.
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公开(公告)号：US10157351B1
公开(公告)日：2018-12-18
申请号：US14918444
申请日：2015-10-20
Applicant: Amazon Technologies, Inc.
Inventor： Rajeev Ramnarain Rastogi , Varnit Agnihotri , Rushi Bhatt , Srujana Merugu
Abstract: Data mining systems and methods are disclosed for associating users with items based on underlying personas. The system associates each user account with one or more underlying personas that contribute to the user's interactions with different items, and predicts an active persona for a user based on the user's recent interactions with items and make item related recommendations that are oriented to the active persona. Thus, for example, even though multiple individuals may share a computer and/or account, the content (e.g., item recommendations) presented during a browsing session may be based primarily or exclusively on the past browsing behaviors of the particular individual conducting the browsing session.
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公开(公告)号：US10354201B1
公开(公告)日：2019-07-16
申请号：US14990171
申请日：2016-01-07
Applicant: Amazon Technologies, Inc.
Inventor： Gourav Roy , Amit Chandak , Prateek Gupta , Srujana Merugu , Aswin Natarajan , Sathish Kumar Palanisamy , Gowda Dayananda Anjaneyapura Range , Jagannathan Srinivasan , Bharath Venkatesh
Abstract: A number of attributes of different attribute types, to be used to assign observation records of a data set to clusters, are identified. Attribute-type-specific distance metrics for the attributes, which can be combined to obtain a normalized aggregated distance of an observation record from a cluster representative, are selected. One or more iterations of a selected clustering methodology are implemented on the data set using resources of a machine learning service until targeted termination criteria are met. A given iteration includes assigning the observations to clusters of a current version of a clustering model based on the aggregated distances from the cluster representatives of the current version, and updating the cluster representatives to generate a new version of the clustering model.
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