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    FIELD CONTENT BASED PATTERN GENERATION FOR HETEROGENEOUS LOGS
    11.
    发明申请
    FIELD CONTENT BASED PATTERN GENERATION FOR HETEROGENEOUS LOGS 审中-公开

    公开(公告)号：WO2018195252A1

    公开(公告)日：2018-10-25

    申请号：PCT/US2018/028266

    申请日：2018-04-19

    Applicant: NEC LABORATORIES AMERICA, INC.

    Inventor： DEBNATH, Biplob ,  ZHANG, Hui

    IPC: G06F11/34

    CPC classification number: G06F11/34 ,  G06F11/0775 ,  G06F11/079 ,  G06F11/3072 ,  G06F16/35 ,  G06F2201/86

    Abstract: A system and method are provided for pattern discovery in input heterogeneous logs having unstructured text content and one or more fields. The system includes a memory (810). The system further includes a processor (804) in communication with the memory. The processor runs program code to preprocess the input heterogeneous logs to obtain pre-processed logs by splitting the input heterogeneous logs into tokens. The processor runs program code to generate seed patterns from the preprocessed logs. The processor runs program code to generate final patterns by specializing a selected set of fields in each of the seed patterns to generate a final pattern set.

    DISCOVERING CRITICAL ALERTS THROUGH LEARNING OVER HETEROGENEOUS TEMPORAL GRAPHS
    15.
    发明申请
    DISCOVERING CRITICAL ALERTS THROUGH LEARNING OVER HETEROGENEOUS TEMPORAL GRAPHS 审中-公开

    公开(公告)号：WO2018093807A1

    公开(公告)日：2018-05-24

    申请号：PCT/US2017/061664

    申请日：2017-11-15

    Applicant: NEC LABORATORIES AMERICA, INC

    Inventor： ZONG, Bo ,  TANG, LuAn ,  SONG, Qi ,  DEBNATH, Biplob ,  ZHANG, Hui ,  JIANG, Guofei

    IPC: G06N3/08 ,  G06F11/34

    Abstract: A method is provided that includes transforming training data into a neural network based learning model using a set of temporal graphs derived from the training data. The method includes performing model learning on the learning model by automatically adjusting learning model parameters based on the set of the temporal graphs to minimize differences between a predetermined ground-truth ranking list and a learning model output ranking list. The method includes transforming testing data into a neural network based inference model using another set of temporal graphs derived from the testing data. The method includes performing model inference by applying the inference and learning models to test data to extract context features for alerts in the test data and calculate a ranking list for the alerts based on the extracted context features. Top-ranked alerts are identified as critical alerts. Each alert represents an anomaly in the test data.

    RECOMMENDER SYSTEM FOR HETEROGENEOUS LOG PATTERN EDITING OPERATION
    16.
    发明申请
    RECOMMENDER SYSTEM FOR HETEROGENEOUS LOG PATTERN EDITING OPERATION 审中-公开
    异构日志模式编辑操作的推荐系统

    公开(公告)号：WO2018039446A1

    公开(公告)日：2018-03-01

    申请号：PCT/US2017/048406

    申请日：2017-08-24

    Applicant: NEC LABORATORIES AMERICA, INC.

    Inventor： XU, Jianwu ,  DEBNATH, Biplob ,  ZONG, Bo ,  ZHANG, Hui ,  JIANG, Guofei ,  GE, Hancheng

    IPC: G06F11/34

    CPC classification number: G06N5/047 ,  G06F17/16 ,  G06F17/20 ,  G06F17/2282 ,  G06F17/277 ,  G06N7/00

    Abstract: A heterogeneous log pattern editing recommendation system and computer- implemented method are provided. The system (600) has a processor (605) configured to identify, from heterogeneous logs, patterns including variable fields and constant fields. The processor (605) is also configured to extract a category feature, a cardinality feature, and a before-after n-gram feature by tokenizing the variable fields in the identified patterns. The processor (605) is additionally configured to generate target similarity scores between target fields to be potentially edited and other fields from among the variable fields in the heterogeneous logs using pattern editing operations based on the extracted category feature, the extracted cardinality feature, and the extracted before-after n-gram feature. The processor (605) is further configured to recommend, to a user, log pattern edits for at least one of the target fields based on the target similarity scores between the target fields in the heterogeneous logs.

    Abstract translation: 提供了异构日志模式编辑推荐系统和计算机实现的方法。 系统（600）具有配置成从异构日志中识别包括可变字段和常量字段的模式的处理器（605）。 处理器（605）还被配置为通过对所识别的模式中的变量字段进行标记来提取类别特征，基数特征以及之前后的n元特征。 处理器（605）另外被配置为使用基于提取的类别特征，提取的基数特征和基于所提取的类别特征的模式编辑操作，从而在可能编辑的目标字段与异构日志中的可变字段之中的其他字段之间生成目标相似度分数 在n-gram特征前后提取。 处理器（605）还被配置为基于异构日志中的目标字段之间的目标相似度分数向用户推荐至少一个目标字段的日志模式编辑。

    FAST PATTERN DISCOVERY FOR LOG ANALYTICS
    17.
    发明申请
    FAST PATTERN DISCOVERY FOR LOG ANALYTICS 审中-公开
    用于LOG分析的快速模式发现

    公开(公告)号：WO2017087437A1

    公开(公告)日：2017-05-26

    申请号：PCT/US2016/062135

    申请日：2016-11-16

    Applicant: NEC LABORATORIES AMERICA, INC.

    Inventor： DEBNATH, Biplob ,  XU, Jianwu ,  ZHANG, Hui ,  JIANG, Guofei ,  HAMOONI, Hossein

    IPC: G06F11/34

    CPC classification number: G06K9/4604 ,  G06F11/34 ,  G06F17/30625 ,  G06F17/40

    Abstract: Systems and methods are disclosed for parsing logs from arbitrary or unknown systems or applications by capturing heterogeneous logs from the arbitrary or unknown systems or applications; generating one pattern for every unique log message; building a pattern hierarchy tree by grouping patterns based on similarity metrics, and for every group it generates one pattern by combing all constituting patterns of that group; and selecting a set of patterns from the pattern hierarchy tree.

    Abstract translation: 公开了系统和方法，用于通过从任意或未知系统或应用程序捕获异构日志来解析来自任意或未知系统或应用程序的日志; 为每个唯一的日志消息生成一个模式; 通过基于相似性度量对模式进行分组来构建模式层次树，并且对于每个组，通过组合所有组成模式来生成一个模式; 并从模式层次树中选择一组模式。

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