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    Data mining system for assessing pairwise item similarity
    2.
    发明授权
    Data mining system for assessing pairwise item similarity 有权

    公开(公告)号：US10162868B1

    公开(公告)日：2018-12-25

    申请号：US14657915

    申请日：2015-03-13

    Applicant: Amazon Technologies, Inc.

    Inventor： Giovanni Zappella

    IPC: G06F17/30

    Abstract: Data mining systems and methods are disclosed for evaluating pairwise substitutability relationships among items. For example, a pairwise similarity measure may correspond to a value quantifying the extent to which an item A is favored over an item B by a population of users. Given a base item selected by a user, the system may select a candidate item from a set of potential substitute items for the base item based on current estimates of corresponding pairwise similarities. The system may then present the candidate item to the user in a context of comparison against the base item and obtain an indication of user preference between the two. The system may then update corresponding pairwise similarities based on the indication of preference.

    Techniques for content selection in seasonal environments
    3.
    发明授权
    Techniques for content selection in seasonal environments 有权

    公开(公告)号：US11586965B1

    公开(公告)日：2023-02-21

    申请号：US16858241

    申请日：2020-04-24

    Applicant: Amazon Technologies, Inc.

    Inventor： Giuseppe Di Benedetto ,  Vito Bellini ,  Giovanni Zappella

    IPC: G06N20/00 ,  G06N7/00 ,  G06F16/635 ,  G06F16/2457 ,  G06N5/04 ,  G06F16/9535

    Abstract: Techniques are described herein for generating adaptive recommendations in response to a content request. The system herein detects abrupt changes and leverages the seasonality of a reward function. A collection of contextual models are utilized, each one learning about one of the unique reward stationary states. A short-term memory model is used to detect reward shifts toward stationary periods that have not occurred in the past. In this case, a new base bandit instance is initialized. In order to perform the change point detection, at each step every model gets assigned a score indicating how likely the last observation is to come from a corresponding stationary period represented by a respective model. A model is selected based on the scores. The model provides a recommendation and the system can monitor clickstream data to identify the reward for providing the recommendation.

    Artificial intelligence system incorporating automatic model switching based on model parameter confidence sets
    6.
    发明授权
    Artificial intelligence system incorporating automatic model switching based on model parameter confidence sets 有权

    公开(公告)号：US11164093B1

    公开(公告)日：2021-11-02

    申请号：US16054817

    申请日：2018-08-03

    Applicant: Amazon Technologies, Inc.

    Inventor： Giovanni Zappella

    IPC: G10L15/22 ,  G10L15/32 ,  G10L15/26 ,  G06N99/00 ,  G06Q30/02 ,  G06N5/04 ,  G06N20/00 ,  G06F30/20

    Abstract: Computer systems and associated methods are disclosed to implement a model executor that dynamically selects machine learning models for choosing sequential actions. In embodiments, the model executor executes and updates an active model to choose sequential actions. The model executor periodically initiates a recent model and updates the recent model along with the active model based on recently chosen actions and results of the active model. The model executor periodically compares respective confidence sets of the two models' parameters. If the two confidence sets are sufficiently divergent, a replacement model is selected to replace the active model. In embodiments, the replacement model may be selected from a library of past models based on their similarity with the recent model. In embodiments, past models that exceed a certain age or have not been recently used as the active model are removed from the library.

    Generation and use of literary work signatures reflective of entity relationships
    8.
    发明授权
    Generation and use of literary work signatures reflective of entity relationships 有权

    公开(公告)号：US11599822B1

    公开(公告)日：2023-03-07

    申请号：US16443477

    申请日：2019-06-17

    Applicant: Amazon Technologies, Inc.

    Inventor： Giovanni Zappella

    IPC: G06N20/00 ,  G06F16/951 ,  H04L67/10

    Abstract: A computer system and process extract information from a literary work regarding relationships between entities (e.g., characters, locations, etc.) described or represented in the literary work, and generate a graph representing these relationships. The graph data is parsed into sub-graphs, and the subgraphs are used to generate a signature of the literary work. The respective signatures of different literary works may be compared for purposes of generating literary work recommendations for users.

    Machine learning-based literary work ranking and recommendation system
    9.
    发明授权
    Machine learning-based literary work ranking and recommendation system 有权

    公开(公告)号：US10366343B1

    公开(公告)日：2019-07-30

    申请号：US14657931

    申请日：2015-03-13

    Applicant: Amazon Technologies, Inc.

    Inventor： Giovanni Zappella

    IPC: G06N20/00 ,  H04L29/08 ,  G06F16/951

    Abstract: A system ranks and/or recommends literary works based on information extracted from the text of the literary works. For example, the system may use information extracted from the text of a literary work to generate a graph representing the relationships of entities in the literary work. The system may identify sub-graphs in the graph, and generate a signature based on the values associated with the various sub-graphs. The system may generate signatures of a plurality of literary works. The system may then retrieve the signature of a literary work that was highly rated by a user, and compare the retrieved signature with other generated signatures using machine-learning algorithms to select literary works to recommend to the user.

    Optimized selection and delivery of content
    10.
    发明授权
    Optimized selection and delivery of content 有权

    公开(公告)号：US10242381B1

    公开(公告)日：2019-03-26

    申请号：US14661996

    申请日：2015-03-18

    Applicant: Amazon Technologies, Inc.

    Inventor： Giovanni Zappella ,  Cedric Philippe Charles Jean Ghislain Archambeau

    IPC: G06Q30/00 ,  G06Q30/02 ,  H04L12/58 ,  G06F17/30 ,  G05B19/418

    Abstract: Technologies for optimized selection of content for delivery to a user that both optimizes the expected return from the delivery of the content to the user and that enables exploration of delivery of new content to users are disclosed. Content is selected for delivery to a user based on an exploitation score that defines an estimate of the feedback expected from the delivery of the content to the user and an exploration score that varies inversely with the number of times that the content has been transmitted to all users. The use of the exploration score enables the exploration of delivery of new content to users. The content might be delivered via e-mail messages, a web site, or using another mechanism.

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