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    METHOD AND SYSTEM OF AUTOMATIC EVENT AND ERROR CORRELATION FROM LOG DATA
    1.
    发明申请
    METHOD AND SYSTEM OF AUTOMATIC EVENT AND ERROR CORRELATION FROM LOG DATA 审中-公开

    公开(公告)号：US20190073257A1

    公开(公告)日：2019-03-07

    申请号：US15823259

    申请日：2017-11-27

    Applicant: Infosys Limited

    Inventor： Sudipto Shankar Dasgupta ,  Mayoor Rao ,  Ganapathy Subramanian

    IPC: G06F11/07 ,  G06F11/34 ,  G06F17/30

    Abstract: A method and system can implement error and event log correlation in an apparatus and include extracting one or more log information associated with a storage location and creating a flexible structure of the one or more log information. The one or more log information is translated to a database store based on a user input. A match level is determined between an event and error data through the one or more log information extracted. When the match level exceeds a predetermined value, a relationship between the event and error data is created through an algorithm and a shareable entry is created for the relationship in a format usable by another apparatus.

    AUTOMATED SYSTEM FOR DEVELOPMENT AND DEPLOYMENT OF HETEROGENEOUS PREDICTIVE MODELS
    2.
    发明申请
    AUTOMATED SYSTEM FOR DEVELOPMENT AND DEPLOYMENT OF HETEROGENEOUS PREDICTIVE MODELS 审中-公开

    公开(公告)号：US20180075357A1

    公开(公告)日：2018-03-15

    申请号：US15473285

    申请日：2017-03-29

    Applicant: Infosys Limited

    Inventor： Ganapathy Subramanian ,  Sudipto Shankar Dasgupta ,  Kiran Kumar Kaipa ,  Prasanna Nagesh Teli

    IPC: G06N5/04 ,  G06N99/00

    CPC classification number: G06N20/00

    Abstract: A method and/or system for heterogeneous predictive models generation based on sampling of big data is disclosed. The method involves receiving a dataset and a target column associated with the dataset at a data processing engine from a distributed data warehouse. One or more columns associated with the dataset are classified at the data processing engine as a categorical column or a continuous column. One or more parameters in the dataset are identified to extract a sample data from the dataset. The sample data from the dataset is extracted based on the identified one or more parameters. One or more rank ordered machine learning algorithms are recommended to one or more users, to generate one or more predictive models from the sample data. One or more heterogeneous predictive models are generated based on the rank ordered algorithm through one or more iterations.

    SYSTEM AND METHOD OF DATA JOIN AND METADATA CONFIGURATION
    4.
    发明申请
    SYSTEM AND METHOD OF DATA JOIN AND METADATA CONFIGURATION 审中-公开
    数据加密和元数据配置的系统和方法

    公开(公告)号：US20170060950A1

    公开(公告)日：2017-03-02

    申请号：US15247659

    申请日：2016-08-25

    Applicant: Infosys Limited

    Inventor： Navin Budhiraja ,  Sudipto Shankar Dasgupta ,  Sameer Mahadeo Kolhatkar ,  Mayoor Rao ,  Arulkumar Gopalan

    IPC: G06F17/30

    Abstract: A method and system of a data join includes capture of metadata information associated with one of semi-structured data and unstructured data. A flattened structure for one of the semi-structured data and the unstructured data is defined, and an entity is extracted from the unstructured data. Further, one of the semi-structured data and an entity extracted unstructured data are flattened based on the flattened structure, and flattened semi-structured data and flattened entity extracted unstructured data with relational data are joined.

    Abstract translation: 数据连接的方法和系统包括捕获与半结构化数据和非结构化数据之一相关联的元数据信息。 定义了半结构化数据和非结构化数据之一的扁平化结构，并从非结构化数据中提取实体。 此外，基于扁平化结构，半结构化数据和实体提取的非结构化数据之一被平坦化，并且连接具有关系数据的平坦化半结构化数据和平坦化实体提取的非结构化数据。

    System and method of generating platform-agnostic abstract syntax tree
    6.
    发明授权
    System and method of generating platform-agnostic abstract syntax tree 有权

    公开(公告)号：US10803083B2

    公开(公告)日：2020-10-13

    申请号：US15247677

    申请日：2016-08-25

    Applicant: Infosys Limited

    Inventor： Navin Budhiraja ,  Sudipto Shankar Dasgupta ,  Mayoor Rao

    IPC: G06F16/25

    Abstract: A method generating a platform-agnostic abstract syntax tree (AST) comprises receiving data in a predefined format, through an input unit; subsequently parsing the data to extract model information corresponding to the predefined format of the data; and transforming, by a processing server, the model information to an abstract syntax tree (AST) structure. The above steps aid in generating, by the processing server, a platform-agnostic AST by combining predefined metadata and the abstract syntax tree (AST) structure.

    SYSTEM AND METHOD OF GENERATING PLATFORM-AGNOSTIC ABSTRACT SYNTAX TREE
    9.
    发明申请
    SYSTEM AND METHOD OF GENERATING PLATFORM-AGNOSTIC ABSTRACT SYNTAX TREE 审中-公开
    生成平台摘要语法树的系统和方法

    公开(公告)号：US20170060910A1

    公开(公告)日：2017-03-02

    申请号：US15247677

    申请日：2016-08-25

    Applicant: Infosys Limited

    Inventor： Navin Budhiraja ,  Sudipto Shankar Dasgupta ,  Mayoor Rao

    IPC: G06F17/30 ,  G06F17/27

    Abstract: A method generating a platform-agnostic abstract syntax tree (AST) comprises receiving data in a predefined format, through an input unit; subsequently parsing the data to extract model information corresponding to the predefined format of the data; and transforming, by a processing server, the model information to an abstract syntax tree (AST) structure. The above steps aid in generating, by the processing server, a platform-agnostic AST by combining predefined metadata and the abstract syntax tree (AST) structure.

    Abstract translation: 生成平台不可知抽象语法树（AST）的方法包括通过输入单元接收预定格式的数据; 随后解析数据以提取对应于数据的预定格式的模型信息; 并通过处理服务器将模型信息转换为抽象语法树（AST）结构。 上述步骤有助于由处理服务器通过组合预定义的元数据和抽象语法树（AST）结构来生成与平台无关的AST。

    Extraction of tokens and relationship between tokens from documents to form an entity relationship map
    10.
    发明授权
    Extraction of tokens and relationship between tokens from documents to form an entity relationship map 有权

    公开(公告)号：US11568142B2

    公开(公告)日：2023-01-31

    申请号：US16371076

    申请日：2019-03-31

    Applicant: Infosys Limited

    Inventor： Sudipto Shankar Dasgupta ,  Mayoor Rao ,  Ganapathy Subramanian ,  Sairam Yeturi

    IPC: G06F17/00 ,  G06F40/284 ,  G06F40/216

    Abstract: A system and method of creating an entity relationship map includes receiving a stream of lexical matter associated with one or more categories (302) and identifying one or more tokens from the received lexical matter based on the one or more categories (304). A frequency of one or more of unique lexical token and recurring lexical token are determined (306) and one or more outliers based on a standard deviation range associated with the at least one category is eliminated (308). Sentences with the one or more recurring lexical tokens are selected (310) to find one or more lexical neighbors and the entity relationship map is created based on an association between the unique lexical tokens and the at least one lexical neighbor (312).

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