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.

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.

An approach is disclosed for generating an adjustable ruleset for fingerprinting data. The approach involves, for example, designating a data type as private. The approach also involves collecting private data relating to user from one or more data sources, wherein the private data includes a plurality of attributes that include a private attribute having the private data type. The approach further involves transforming the private attribute based on one or more configured rules for tokenizing the private attribute. The approach also involves generating a token corresponding to transformed private attribute; and initiating storage of the token for subsequent discovery of data having the private data type.

An approach is disclosed for generating an adjustable ruleset for fingerprinting data. The approach involves, for example, designating a data type as private. The approach also involves collecting private data relating to user from one or more data sources, wherein the private data includes a plurality of attributes that include a private attribute having the private data type. The approach further involves transforming the private attribute based on one or more configured rules for tokenizing the private attribute. The approach also involves generating a token corresponding to transformed private attribute; and initiating storage of the token for subsequent discovery of data having the private data type.

Systems and methods for facilitating an automated customization of user interface are disclosed. The system may include a processor including an AI engine and a UI engine. The AI engine may receive an input data in the form of a pre-defined template that may facilitate the input data to be received in user-readable format. The AI engine may process the pre-defined template to extract input attributes corresponding to the input data. The AI engine may dynamically map the input attributes with sample attributes of a pre-stored file. Based on the dynamic mapping, the AI engine may obtain a form pertaining to an expected visual representation of the web page. The AI engine may facilitate responsive scaling of the form depending on size attributes of the user interface. The UI engine may include a form engine that may customize the form for generation of the web page.

Systems and methods for facilitating an automated customization of user interface are disclosed. The system may include a processor including an AI engine and a UI engine. The AI engine may receive an input data in the form of a pre-defined template that may facilitate the input data to be received in user-readable format. The AI engine may process the pre-defined template to extract input attributes corresponding to the input data. The AI engine may dynamically map the input attributes with sample attributes of a pre-stored file. Based on the dynamic mapping, the AI engine may obtain a form pertaining to an expected visual representation of the web page. The AI engine may facilitate responsive scaling of the form depending on size attributes of the user interface. The UI engine may include a form engine that may customize the form for generation of the web page.

A semantic dependency relationship and/or a syntactic dependency relationship is determined between at least one word of a sentence and any of a set of surrounding words in the sentence. The determined semantic dependency relationship and/or the determined syntactic dependency relationship are provided as input to a machine learning model. One or more outputs of the machine learning model are obtained, the one or more outputs indicating, for a set of candidate edits for the at least one word of the sentence, a grammatical accuracy of each candidate edit of the set of candidate edits in view of the syntactic dependency relationship and/or the syntactic dependency relationship. A candidate edit is selected from the set of candidate edits based on the indicated grammatical accuracy of each candidate edit from the set of candidate edits.

Disclosed is a system, method, and computer program product for implementing a log analytics method and system that can configure, collect, and analyze log records in an efficient manner. An improved approach has been described to automatically generate a log parser by analysis of the line content of a log. In addition, an efficient approach has been described to extract key-value content from the log content.

Disclosed is a system, method, and computer program product for implementing a log analytics method and system that can configure, collect, and analyze log records in an efficient manner. An improved approach has been described to automatically generate a log parser by analysis of the line content of a log. In addition, an efficient approach has been described to extract key-value content from the log content.

A system, method and computer program product for cognitive copy and paste. The method includes: receiving, at a hardware processor of a computer system, an input representing a selection of a content captured from a source application program, and receiving an input representing an identified target application program that will receive the selected content to be copied and rendered in the target application program. The selected content is analyzed to determine a context for the selected content; and a rendering of the selected content at a location within the destination application based on the determined context, the rendering achieving a best representation of the selected content on the destination application. The analyzing includes invoking a natural language processor to determine an intent, meaning, or an intended use of the selected content based on the determined context, and employs a support vector machine for determining a best format change when rendering.