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    AUGMENTED DATA INSIGHT GENERATION AND PROVISION
    2.
    发明申请
    AUGMENTED DATA INSIGHT GENERATION AND PROVISION 审中-公开

    公开(公告)号：WO2022093358A1

    公开(公告)日：2022-05-05

    申请号：PCT/US2021/045629

    申请日：2021-08-12

    Applicant: MICROSOFT TECHNOLOGY LICENSING, LLC

    Inventor： NECKERMANN, Tom ,  WILSON, Alexander James ,  REY, Romain Gabriel Paul

    IPC: G06Q10/10 ,  G06N20/00 ,  G06F16/383

    Abstract: In the present disclosure, artificial intelligence (AI) processing is trained and leveraged to learn user-specific insights that are contextually relevant to a state of a user communication. Contextual information about a state of a user communication may be collected and analyzed. That contextual information may be cross-referenced with an extensive knowledge graph that is constructed from user context data. Exemplary AI processing may further be trained to apply a relevance analysis to assist with processing described herein including generation and curation of data insights that are most relevant to a state of a user communication. In some examples, the data insight generation process may be augmented by pre-generating data insights that may be relevant to a user communication prior to occurrence of the user communication. Further technical examples pertain to the rendering and presentation of representations of data insights through a graphical user interface (GUI).

    EVENT DETECTION BASED ON TEXT STREAMS
    3.
    发明申请
    EVENT DETECTION BASED ON TEXT STREAMS 审中-公开

    公开(公告)号：WO2019245885A1

    公开(公告)日：2019-12-26

    申请号：PCT/US2019/037134

    申请日：2019-06-14

    Applicant: MICROSOFT TECHNOLOGY LICENSING, LLC

    Inventor： WILSON, Alexander James

    IPC: G06F16/35 ,  G06F17/21

    Abstract: A text stream source is accessed that includes a plurality of text content items. Unique word groupings are determined for the plurality of text content items. A burst detection algorithm is executed to determine word groupings that are currently bursting and that started within a specified time period. Based on the word groupings, an issue is determined based on identifying a set of texts forming at least one clique.

    SEMANTIC SPACE SCANNING FOR DIFFERENTIAL TOPIC EXTRACTION
    5.
    发明申请
    SEMANTIC SPACE SCANNING FOR DIFFERENTIAL TOPIC EXTRACTION 审中-公开

    公开(公告)号：WO2020256832A1

    公开(公告)日：2020-12-24

    申请号：PCT/US2020/030160

    申请日：2020-04-27

    Applicant: MICROSOFT TECHNOLOGY LICENSING, LLC

    Inventor： WILSON, Alexander James ,  REY, Romain

    IPC: G06F16/35

    Abstract: A system for extracting differential topics from a dataset including a user interface, a memory for storing executable program code, and one or more electronic processors coupled to the memory and the user interface. The electronics processors are configured to receive a dataset from one or more servers, wherein the dataset comprises user feedback data associated with a software program. The electronic processors are also configured to extract text from the dataset, convert the extracted text to vector data, and determine anomalous data clusters associated with the vector data using statistical analysis. The electronic processors are also configured to differentiate overlapping anomalous data clusters using a classification algorithm, wherein the differentiated overlapping anomalous data clusters are associated with specific topics, and export each specific topic associated with the differentiated overlapping data cluster.

    DYNAMIC MONITORING, DETECTION OF EMERGING COMPUTER EVENTS
    6.
    发明申请
    DYNAMIC MONITORING, DETECTION OF EMERGING COMPUTER EVENTS 审中-公开

    公开(公告)号：WO2020197897A1

    公开(公告)日：2020-10-01

    申请号：PCT/US2020/023469

    申请日：2020-03-19

    Applicant: MICROSOFT TECHNOLOGY LICENSING, LLC

    Inventor： WILSON, Alexander James ,  NECKERMANN, Tom ,  VAN BRUGGEN, Simone

    IPC: H04L29/06 ,  G06F21/55 ,  H04L12/24

    Abstract: Technologies are provided for the monitoring, detection, and notification of emerging, related issues within a system, which may indicate a problem. Within a computing-security system, a sudden increase in the frequency of events associated with unauthorized logon attempts signal a real-time and ongoing security risk. A method monitors system-related events and generates a vector representation for each event based on event features. Clusters of related events are determined, and a state automaton is employed to determine a strength of temporal "bursty" activity for each cluster. Hypothesis testing is performed on each cluster to determine a likelihood that the cluster is a temporally emergent cluster. Clusters with a bursting likelihood above a threshold are determined to be an emergent cluster associated with an anomalous issue. A notification regarding the detected anomaly is provided. A remedial action addressing the anomaly is performed. Noisy clusters are filtered and aggregated based on their bursting likelihood and overlapping sub-spaces of the hyperspace.

    MACHINE LEARNING APPLICATIONS FOR TEMPORALLY-RELATED EVENTS
    7.
    发明申请
    MACHINE LEARNING APPLICATIONS FOR TEMPORALLY-RELATED EVENTS 审中-公开

    公开(公告)号：WO2020123323A1

    公开(公告)日：2020-06-18

    申请号：PCT/US2019/065118

    申请日：2019-12-08

    Applicant: MICROSOFT TECHNOLOGY LICENSING, LLC

    Inventor： WILSON, Alexander James ,  NECKERMANN, Tom ,  VAN BRUGGEN, Simone

    IPC: G06F40/30 ,  G06F40/284 ,  G06F11/07 ,  G06F16/332

    Abstract: Systems and methods for enhanced classification of sequences of objects based on clique similarity and metadata associated with the sequences are presented. Sequences are received. Events are detected based on analyzing k-skip-n-grams included in the sequences. For each event of the detected plurality of events, a graph is generated. The graph for a particular event includes z-cliques that correspond to portions of the k-skip-n-grams that are included in the sequences that are associated with the particular event. A first sequence, which is separate from the other sequences, is received. The first sequence includes a first plurality of k-skip-n-grams. A trained classifier is employed to classify the first sequence as being associated with a first event of the detected events. Classifying the first sequence is based on a comparison between the first plurality of k-skip-n-grams and the z-cliques of the graph that is generated for the first event.

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