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    COMPOSING HUMAN-READABLE EXPLANATIONS FOR USER NAVIGATIONAL RECOMMENDATIONS
    21.
    发明申请
    COMPOSING HUMAN-READABLE EXPLANATIONS FOR USER NAVIGATIONAL RECOMMENDATIONS 有权

    公开(公告)号：US20220350846A1

    公开(公告)日：2022-11-03

    申请号：US17302429

    申请日：2021-05-03

    Applicant: Oracle International Corporation

    Inventor： Amir Hossein Rezaeian ,  Alberto Polleri

    IPC: G06F16/954 ,  G06N20/00 ,  G06F17/18

    Abstract: Techniques for generating human-readable explanations (also referred to herein as “reasons”) for navigational recommendations are disclosed. Composing a human-readable explanation includes individually selecting words or phrases that are then analyzed, combined, rearranged, modified, or removed to generate the human-readable explanation for a navigational recommendation. A decoder trains a machine learning model to generate the human-readable reasons for the navigational recommendations based on (1) historical recommendation vectors, and (2) historical human-readable reasons associated with the recommendation vectors. The system generates a dictionary of human-readable reasons for recommendations, with each entry of the dictionary including: (1) a recommendation identifier (ID) associated with a recommended navigational target, (2) a reason identifier (ID) associated with a particular reason for the recommendation, and (3) a human-readable reason associated with the reason ID.

    ANOMALOUS EVENT PREDICTION USING CONTRASTIVE LEARNING
    28.
    发明公开
    ANOMALOUS EVENT PREDICTION USING CONTRASTIVE LEARNING 审中-公开

    公开(公告)号：US20230298371A1

    公开(公告)日：2023-09-21

    申请号：US17654891

    申请日：2022-03-15

    Applicant: Oracle International Corporation

    Inventor： Amir Hossein Rezaeian ,  Alberto Polleri

    IPC: G06V30/413 ,  G06V10/774 ,  G06N3/04

    CPC classification number: G06V30/413 ,  G06V10/774 ,  G06N3/0454

    Abstract: Various techniques can include systems and methods for using contrastive learning to predict anomalous events in data processing systems. The method can include accessing an unstructured data file and contextual data associated with the unstructured data file. The method can also include generating an event-data input element for the unstructured data file. The event-data input element can include a set of feature vectors. The set of feature vectors can include a first feature vector generated by using a first encoder to process the unstructured file and a second feature vector generated by using a second encoder to process the contextual data. The method can also include generating a classification result of the unstructured data file by using a machine-learning model to process the event-data input element, in which the classification result includes a prediction of whether the particular event corresponds to an anomalous event.

    USER DISCUSSION ENVIRONMENT INTERACTION AND CURATION VIA SYSTEM-GENERATED RESPONSES
    30.
    发明申请
    USER DISCUSSION ENVIRONMENT INTERACTION AND CURATION VIA SYSTEM-GENERATED RESPONSES 有权

    公开(公告)号：US20220391595A1

    公开(公告)日：2022-12-08

    申请号：US17470179

    申请日：2021-09-09

    Applicant: Oracle International Corporation

    Inventor： Oleg Gennadievich Shevelev ,  Alberto Polleri ,  Marc Michiel Bron

    IPC: G06F40/40 ,  G06N5/04 ,  G06N5/02

    Abstract: Techniques for interacting with users in a discussion environment are disclosed. Upon identifying a question in the discussion environment, a system determines: (a) whether a stored answer has already been associated with the question, (b) whether an answer can be generated by the system using existing information accessible to the system, or (c) whether to contact an expert to answer the question. The system updates the knowledge base by storing the questions and answers, along with user feedback to the questions and answers. Based on the user feedback, the system determines whether to modify existing answers to user-generated questions or to seek answers from additional human experts.

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