Abstract: A method and system for authenticating software licenses of a software includes a request for a software authentication received from one or more software subscribers and one or more electronic licenses distributed between one or more software vendors and the one or more software subscribers. Further, one or more tokens are validated through an authentication engine at a delivery packet delivered to the software subscriber. A license key associated with each validated token is generated and distributed through a licensing engine. The software is initiated to be enabled through the license key.

Abstract: A computer implemented system and method for generating a platform agnostic digital worker includes identifying a task to be performed by the digital worker. A specification for the digital worker is generated that comprises at least a predefined standard for configuration of input and output parameters and error handling. A digital worker created by an agent based on the specification is received to deploy the digital worker at an orchestration engine. The digital worker is sequenced into a repository of digital workers in a predefined manner of workflow, where the digital worker is configured to execute sequentially to perform a scheduled task.

Abstract: A computer implemented a method and system for enrichment of OCR extracted data is disclosed comprising of accepting a set of extraction criteria and a set of configuration parameters by a data extraction engine. The data extraction engine captures data satisfying an extraction criteria using the configuration parameters and adapts the captured data using a set of domain specific rules and a set of OCR error patterns. A learning engine generates learning data models using the adapted data and the configuration parameters and the system dynamically updates the extraction criteria using the generated learning data models. The extraction criteria comprise one or more extraction templates wherein an extraction template includes one of a regular expression, geometric markers, anchor text markers and a combination thereof.

Abstract: Hashing data using an image by performing a bit by bit concatenation of input text and hash key. The result is concatenated bit by bit with the salt. A two bit by two bit multiplication between the result and the reverse of the result is performed to get a next output. The bits of this output are used as coordinates to extract pixel and RGB values from an image. The extracted values are merged to form a string. The string is truncated to a desired length, and then split into two equal strings. A bit by bit concatenation is performed on the split strings to get a hash output.

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.

Abstract: A method, a system and a computer program product for regression test selection in a multi-threaded distributed target program execution tested by multi-threaded test suites. The method includes monitoring changes to source code of the target program in real-time to determine changed code-modules and extracting the regression test cases which simulate the changed code-modules. A calibration engine according to an embodiment isolates test case execution flow at individual test case level and builds relationship between the test case of the multi-threaded test suite and the distributed target program code-modules simulated by the test case. The method enhances the run-time behavior of the target program execution engines and builds relationships between the threads executing in the engine through throttling mechanism without affecting the actual functional execution. It enables calibration to happen in a multi-threaded test environment.

Abstract: Onboarding a Virtual Network Function (VNF) package utilized by multiple network services is disclosed. The VNF package is received from a vendor for network services requested by a customer. The VNF package and its contents may be uploaded on an orchestrating manager, and a NFVI admin decides workflows for the VNF package, for validating and certifying the VNF package. The VNF package is validated using multiple checks and then parameters are identified for monitoring and certifying the VNF package. The VNF package is then ready for onboarding and instantiating the network services requested by the customer.

Abstract: The disclosure provides activation of end to end virtual network services, along with various validations. This technology uses model driven architecture to convert the configurations to VNF/PNF specific commands and abstract the complexity of different types of syntax & command lines. This technology also provides test and diagnostic functionality including service connectivity check, performance, rate-limiting at each step of configuration at virtual infrastructure and functional level. Once the VNS is successfully applied, the configuration will be updated in database which can be referred for any future updates.

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.

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: 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: Automated fault correction in a network environment comprises identifying a pattern in a set of network events and generating a set of substantiating data for the identified patterns. The method can also identify an occurrence probability value for each network event and generate root cause data based on a ranking for the network events using a set of parameters including the occurrence probability. The method can also be directed to performing a regression of the root cause data against a set of historic data and selecting the root cause with a predefined accuracy as an acceptable candidate. The acceptable candidate is then provided for assisted learning for automated fault correction.

Abstract: A system and method of recognizing data in a table area from unstructured data includes a computer network, one or more processors communicatively coupled with the computer network, a storage location, and a graph-theoretic engine that receives an input stream of unstructured data associated. A table area is recognized from unstructured data, through one or more computer processors, from an input stream of unstructured data received over a computer network. One or more table headers associated with the detected one or more table areas are recognized. Further, one or more column delimiters associated with each column of the detected one or more table areas are determined. One or more tabular data associated with the detected one or more table areas are extracted. The extracted tabular data is mapped to one or more target schema to store onto a relational database.

Abstract: This technique improves energy efficiency of MapReduce system by using system performance model without changing any component of the MapReduce system. This involves determining presence of any hardware bottleneck in any node of MapReduce system based on a system performance model and if any hardware bottleneck is present in any node, then the maximum bandwidth value of hardware associated with the bottleneck of each node is determined. Thereafter, an energy efficient value of Central Processing Unit (CPU) frequency of each node having the bottleneck is determined by using the system performance model and the maximum bandwidth value of hardware associated with the bottleneck. Further, the CPU frequency of each node having the bottleneck is set at the energy efficient value determined in the earlier step.

Abstract: This technology relates to a device, method, and non-transitory computer readable medium for allocating one or more resources optimally in a composite cloud environment. This technology involves configuring organization and service level quota values, describing service composition, service unit, service level agreement, defining allocation model and resource allocation optimization algorithm. Based on these predefined rules the infrastructure, software and manual resources are assigned, future allocation is forecasted and resources are allocated to complete the service requests received from the users.

Abstract: A method and system automates training named entity recognition in natural language processing to build configurable entity definitions includes receiving input documents or entities through an administration module and defining a domain for each entity. Further, one or more entities corresponding to the domain specific entity in the received documents are determined and a training file to one of pick a right parser, extract content and label the entity ambiguity is generated. One or more user actions are collected and maintained at a repository through a knowledge engine. Still further, one or more labelled ambiguous words are predicted and the knowledge engine is updated. Data may be fetched, through a training pipeline execution engine and each entity may be associated with one or more documents based on the fetched data from the document store to build configurable entity definitions.

Abstract: The technique relates to a system and method for data-driven anomaly detection. This technique involves identifying region of interest from the data based on dimensionality reduction technique and change point detection algorithm. A reference data can be obtained separately or can be obtained from the test data also, wherein the reference data represent the normal operating condition of a system. The reference data are classified into different groups representing different modes of operation of the system. A control limit is determined for the different groups. The data within the region of interest are mapped with the different groups of the reference data and it is determined if the mapped data fall outside of the control limit of the mapped group. Finally, at least one abnormal event is detected by applying a heuristic algorithm on the data within the region of interest which are outside the control limit.

Abstract: A computer implemented a method and system for enrichment of OCR extracted data is disclosed comprising of accepting a set of extraction criteria and a set of configuration parameters by a data extraction engine. The data extraction engine captures data satisfying an extraction criteria using the configuration parameters and adapts the captured data using a set of domain specific rules and a set of OCR error patterns. A learning engine generates learning data models using the adapted data and the configuration parameters and the system dynamically updates the extraction criteria using the generated learning data models. The extraction criteria comprise one or more extraction templates wherein an extraction template includes one of a regular expression, geometric markers, anchor text markers and a combination thereof.

Abstract: A system and method for regulating the flow of an electronic message in a social network comprises: creating the electronic message posted by a user in a social network, associating various permissions with the electronic message, notifying the user, information relating to flow of the electronic message from the user in the social network to other user, creating the path of the electronic message flow from the user in the social network to the other user and traversing the path of the electronic message flow from the user in the social network to the other user.

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).