VISUAL REPRESENTATION FOR HIGHER DIMENSION DATA SETS

    公开(公告)号:US20240037321A1

    公开(公告)日:2024-02-01

    申请号:US17878116

    申请日:2022-08-01

    IPC分类号: G06F40/137 G06F16/84

    CPC分类号: G06F40/137 G06F16/84

    摘要: A method for adding dimensions to a visual representation is disclosed. In one embodiment, such a method obtains a data set containing data in a plurality of rows and columns (i.e., dimensions). The method divides the dimensions into a plurality of groups and determines a coordinate system for each group. For each row in the data set, the method determines data points for each group in the corresponding coordinate system. The method then connects the data points for each row with lines to create a visual representation for the data set. In certain embodiments, each group in the data set utilizes a two-dimensional coordinate system. In other embodiments, each group in the data set utilizes a three-dimensional coordinate system. In yet other embodiments, a mix of two-dimensional coordinate systems and three-dimensional coordinate systems are used. A corresponding system and computer program product are also disclosed.

    OFFLINE INTERACTIVE NATURAL LANGUAGE PROCESSING RESULTS

    公开(公告)号:US20230394224A1

    公开(公告)日:2023-12-07

    申请号:US18454451

    申请日:2023-08-23

    申请人: Patent Bots, Inc.

    摘要: Interactive natural language processing (NLP) results may be generated that allow a user to interact with the NLP results but do so in an offline manner so that the documents being processed need not be stored online. To provide interactive NLP results, event handlers may be attached to elements of the NLP results. A user may then select a word or phrase of the NLP results to cause computer software provided with the NLP to present the interactive features. For example, a user may click on a definite noun phrase to view information for diagnosing antecedent basis errors. For another example, a user may click on a word to view information about how that word is used in a document, such as viewing portions of the document that include the word or variants of the word.

    Offline interactive natural language processing results

    公开(公告)号:US11768995B2

    公开(公告)日:2023-09-26

    申请号:US17532122

    申请日:2021-11-22

    申请人: Patent Bots, Inc.

    摘要: Interactive natural language processing (NLP) results may be generated that allow a user to interact with the NLP results but do so in an offline manner so that the documents being processed need not be stored online. To provide interactive NLP results, event handlers may be attached to elements of the NLP results. A user may then select a word or phrase of the NLP results to cause computer software provided with the NLP to present the interactive features. For example, a user may click on a definite noun phrase to view information for diagnosing antecedent basis errors. For another example, a user may click on a word to view information about how that word is used in a document, such as viewing portions of the document that include the word or variants of the word.

    RULES/MODEL-BASED DATA PROCESSING SYSTEM FOR INTELLIGENT EVENT PREDICTION IN AN ELECTRONIC DATA INTERCHANGE SYSTEM

    公开(公告)号:US20230267269A1

    公开(公告)日:2023-08-24

    申请号:US18310409

    申请日:2023-05-01

    申请人: Open Text GXS ULC

    摘要: A system for electronic data interchange (EDI) management includes a memory for storing the EDI document data and a machine learning model representing a set of features of EDI documents and a corresponding status. The system further includes a processor and a non-transitory computer readable medium storing instructions for: accessing an EDI file, the EDI file comprising envelope metadata for an envelope and a first EDI document: and translating the EDI file into a first translated EDI document containing the envelope metadata and a set of EDI document data extracted from the first EDI document, the first translated EDI document formatted according to a hierarchical structure comprising attributes translatable into features processable by the machine learning model to determine a status of the first EDI document.