DIALOG DATA PROCESSING
    1.
    发明申请

    公开(公告)号:US20220092403A1

    公开(公告)日:2022-03-24

    申请号:US17024788

    申请日:2020-09-18

    Abstract: A method, system, and computer program product processes dialog data. The method includes obtaining dialog data including heterogeneous data items. The method includes generating a heterogeneous network based on the dialog data. The heterogeneous network includes two or more bipartite subnetworks representing the relationship of the data items in the dialog data. The nodes of the two or more bipartite subnetworks correspond to the data items in the dialog data. The method includes determining node representations for the nodes in the heterogeneous network through representation learning.

    RESOURCE CONSUMPTION CONTROL
    2.
    发明申请

    公开(公告)号:US20190132258A1

    公开(公告)日:2019-05-02

    申请号:US15802023

    申请日:2017-11-02

    Abstract: A method, computer program product, and system are provided. A resource exhaustion is predicted based on the available resource and a consumption speed of the resource in a bare-metal server. Then it is determined whether the resource exhaustion will have an impact on the Service Level Agreement (SLA) and, responsive to the determination that the resource exhaustion will have an impact on the SLA, a control of the resource consumption speed is enacted to slow down the resource exhaustion and to maintain the SLA.

    NORMALIZATION OF MEDICAL TERMS WITH MULTI-LINGUAL RESOURCES

    公开(公告)号:US20210081502A1

    公开(公告)日:2021-03-18

    申请号:US16569874

    申请日:2019-09-13

    Abstract: Method and apparatus are presented for receiving a medical or medical condition related input term or phrase in a source language, and translating the term or phrase from the source language into at least one target language to obtain a set of translated terms of the input term. For each translated term in the set of translations, the method and apparatus further translate the set of translations back into the source language to obtain an output list of standard versions of the input term, scoring each entry of the output list as to probability of being the most standard version of the input term, and providing the entry of the output list that has the highest score to a user.

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