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    Intent resolution for chatbot conversations with negation and coreferences
    5.
    发明授权
    Intent resolution for chatbot conversations with negation and coreferences 有权

    公开(公告)号：US11531821B2

    公开(公告)日：2022-12-20

    申请号：US16993257

    申请日：2020-08-13

    Applicant: salesforce.com, inc.

    Inventor： Tian Xie ,  Xinyi Yang ,  Caiming Xiong ,  Wenhao Liu ,  Huan Wang ,  Wenpeng Yin ,  Jin Qu

    IPC: G06F40/30 ,  G10L15/22 ,  H04L51/02

    Abstract: A system performs conversations with users using chatbots customized for performing a set of tasks. The system may be a multi-tenant system that allows customization of the chatbots for each tenant. The system processes sentences that may include negation or coreferences. The system determines a confidence score for an input sentence using an intent detection model, for example, a neural network. The system modifies the sentence to generate a modified sentence, for example, by removing a negation or by replacing a pronoun with an entity. The system generates a confidence score for the modified sentence using the intent detection model. The system determines the intent of the sentence based on the confidence scores of the sentence and the modified sentence. The system performs tasks based on the determined intent and performs conversations with users based on the tasks.

    NEURAL NETWORK BASED ANOMALY DETECTION FOR TIME-SERIES DATA
    7.
    发明申请
    NEURAL NETWORK BASED ANOMALY DETECTION FOR TIME-SERIES DATA 有权

    公开(公告)号：US20220335257A1

    公开(公告)日：2022-10-20

    申请号：US17231015

    申请日：2021-04-15

    Applicant: salesforce.com, inc.

    Inventor： Devansh Arpit ,  Huan Wang ,  Caiming Xiong

    IPC: G06K9/62 ,  G06N3/08

    Abstract: A system uses a neural network to detect anomalies in time series data. The system trains the neural network for a fixed number of iterations using data from a time window of the time series. The system uses the loss value at the end of the fixed number of iterations for identifying anomalies in the time series data. For a time window, the system initializes the neural network to random values and trains the neural network for a fixed number of iterations using the data of the time window. After the fixed number of iterations, the system compares the loss values for various data points to a threshold value. Data points having loss value exceeding a threshold are identified as anomalous data points.

    CUSTOMIZING CHATBOTS BASED ON USER SPECIFICATION
    8.
    发明申请
    CUSTOMIZING CHATBOTS BASED ON USER SPECIFICATION 有权

    公开(公告)号：US20220103491A1

    公开(公告)日：2022-03-31

    申请号：US17037554

    申请日：2020-09-29

    Applicant: salesforce.com, inc.

    Inventor： Xinyi Yang ,  Tian Xie ,  Caiming Xiong ,  Wenhao Liu ,  Huan Wang ,  Kazuma Hashimoto ,  Jin Qu ,  Feihong Wu ,  Yingbo Zhou

    IPC: H04L12/58 ,  G06N3/04 ,  G06K9/62 ,  G06F40/35

    Abstract: A conversation engine performs conversations with users using chatbots customized for performing a set of tasks that can be performed using an online system. The conversation engine loads a chatbot configuration that specifies the behavior of a chatbot including the tasks that can be performed by the chatbot, the types of entities relevant to each task, and so on. The conversation may be voice based and use natural language. The conversation engine may load different chatbot configurations to implement different chatbots. The conversation engine receives a conversation engine configuration that specifies the behavior of the conversation engine across chatbots. The system may be a multi-tenant system that allows customization of the chatbots for each tenant.

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