Extracting knowledge from collaborative support sessions

    公开(公告)号:US11011183B2

    公开(公告)日:2021-05-18

    申请号:US16363215

    申请日:2019-03-25

    Abstract: At a communication server, a first computer device and a second computer device are connected to a collaborative support session configured to support audio communications, screen sharing, and control of the first computer device by the second computer device. Screen sharing video image content is converted to a text sequence with timestamps. A text log with timestamps is generated from the text sequence. Using a command-based machine learning model, a sequence of commands and associated parameters, with timestamps, are determined from the text log. Audio is analyzed to produce speech-based information with timestamps. The command sequence is time-synchronized with the speech-based information based on the timestamps of the command sequence and the timestamps of the speech-based information. A knowledge report for the collaborative support session is generated. The knowledge report includes entries each including a timestamp, commands and associated parameters, and speech-based information that are time-synchronized to the timestamp.

    METHOD AND APPARATUS FOR DETERMINING SHELF-LIFE OF ISSUE DETECTED USING DIGITIZED INTELLECTUAL CAPITAL

    公开(公告)号:US20250077337A1

    公开(公告)日:2025-03-06

    申请号:US18457001

    申请日:2023-08-28

    Abstract: Methods are provided for determining decay rates and/or shelf-lives of intellectual capital (IC) detected issues for only performing actions for expired or about to expire IC detected issues. Specifically, the methods involve performing one or more data collections that include data relating to one or more of a configuration of a computing system or an operation of the computing system and detecting an issue in the computing system based on the data. The issue relates to an anomaly in one or more of the configuration of the computing system or the operation of the computing system. The methods further involve determining a shelf-life for the issue, where the shelf-life indicates an estimated duration of the issue existing in the computing system before redetecting whether the issue is still present and adjusting a next data collection of the one or more data collections based on the shelf-life of the issue.

    TRUST-BASED MODEL FOR DEPLOYING ISSUE IDENTIFICATION AND REMEDIATION CODE

    公开(公告)号:US20250117201A1

    公开(公告)日:2025-04-10

    申请号:US18482138

    申请日:2023-10-06

    Abstract: A method, computer system, and computer program product are provided for selectively deploying code modules for issue identification and remediation tasks. A plurality of code modules is obtained, wherein each code module includes instructions for issue identification and remediation. A trust score for each code module of the plurality of code modules is determined, wherein the trust score includes a first trust score component for issue identification and a second trust score component for issue remediation, and wherein the trust score is based on a source of each code module selected from a group of a human-generated source and an artificial intelligence model-generated source. A particular code module of the plurality of code modules is deployed based on the trust score of the particular code module satisfying a threshold value. The trust score for the particular code module is updated based on results of deploying the particular code module.

    EXTRACTING KNOWLEDGE FROM COLLABORATIVE SUPPORT SESSIONS

    公开(公告)号:US20200312348A1

    公开(公告)日:2020-10-01

    申请号:US16363215

    申请日:2019-03-25

    Abstract: At a communication server, a first computer device and a second computer device are connected to a collaborative support session configured to support audio communications, screen sharing, and control of the first computer device by the second computer device. Screen sharing video image content is converted to a text sequence with timestamps. A text log with timestamps is generated from the text sequence. Using a command-based machine learning model, a sequence of commands and associated parameters, with timestamps, are determined from the text log. Audio is analyzed to produce speech-based information with timestamps. The command sequence is time-synchronized with the speech-based information based on the timestamps of the command sequence and the timestamps of the speech-based information. A knowledge report for the collaborative support session is generated. The knowledge report includes entries each including a timestamp, commands and associated parameters, and speech-based information that are time-synchronized to the timestamp.

    MODEL STRUCTURE EXTRACTION FOR ANALYZING UNSTRUCTURED TEXT DATA

    公开(公告)号:US20210027167A1

    公开(公告)日:2021-01-28

    申请号:US16522871

    申请日:2019-07-26

    Abstract: In one embodiment, a device obtains an output of a machine learning-based anomaly detector for unstructured text. The output of the anomaly detector includes a sequence of text analyzed by the detector and an indication that a portion of the sequence of text was flagged by the detector as an anomaly. The device extracts a context for the anomaly as an n-gram of portions of the sequence of text surrounding the anomaly. The device identifies a structure of the anomaly by identifying anchor portions of the extracted context. The device generates, based on the identified structure, an expression that represents the structure of the anomaly within the unstructured text.

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