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.
September 26, 2019
March 26, 2020
Radha Krishna Pisipati, Jianlin Zhang, Shreyas Bettadapura Guruprasad, Uma Devi Ganugula, Krishnamurty Sai Deepak
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.
March 29, 2017
Date of Patent:
February 11, 2020
Abdul Razack, Sudipto Dasgupta, Mayoor Rao, John Kuriakose
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.
March 19, 2014
Date of Patent:
February 4, 2020
Lokendra Shastri, K. Antony Arokia Durai Raj, Balasubramanian Kanagasabapathi
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).
Abstract: A method and system support dynamic impact analysis of at least one change to at least one functional component of a computer application comprising tracking a historical record of the at least one change, grouping a release dataset and a build dataset for matching with at least one requirement from a requirement data file, generating a plurality of impact records datasets (410) and identifying a nature of change. Further, a plurality of build specific data sets (216) can be generated based on a text corpus (416) related to the at least one change and classifying at least one description based on the nature of change. Further an impact matrix (426) is generated for predicting a potential impact to the at least one test case based on the at least one of a probability of change or a probability of failure.
Abstract: A computer implemented system and method for pro-active application monitoring and alerting using affinity band. To enable pro-active monitoring, the present invention may derive affinity band. The invention accesses performance data generated from monitoring an application associated with one or more transaction and configuring iteration period to derive affinity band. The method provides configuring an interval within iteration period whereby all performance metric values may be aggregated and deriving affinity band for each of the performance metrics. The affinity band may then be used as benchmark or threshold to monitor current values for each of the performance metrics. Alerts may be raised through pro-active monitoring mechanism when the current values of the performance metric go beyond the threshold set, displaying a tendency to rise or go beyond normal values with extent of deviation.
Abstract: Methods, systems and non-transitory computer readable media involves receiving information of a new library from a patch management repository. A symbolic link to the new shared library is created and a request to an application process to replace a shared library is communicated. To replace the shared library, the application process periodically checks reference state of the shared library till it reaches a free-state. When the shared library reaches the free-state, the application process unloads the shared library from memory space and loads the new shared library to the memory space. The application process continues performing one or more pre-define functions during the replacement of the shared library.
Abstract: The technique relates to a method, device, and non-transitory computer readable medium for extracting cross language dependencies and estimating code change impact in software based on a plurality of dependency graphs, a network of the plurality of co-committed files and one or more predefined graph metrics. This technique involves extracting source code and revision history data from repository for construction of plurality of dependency graphs and a network of plurality of co-committed files in order to determine one or more cross language dependencies and code change impact in software system built using multiple programming languages, by analyzing the dependency graphs, the network of co-committed files and one or more predefined graph metrics. Finally, the output is visualized with the help of one or more graph visualization technique.
Abstract: A method and system masks sensitive fields on a cheque image based one or more access privileges assigned to a user. The method involves receiving a cheque image at a cheque masking engine. A cheque template from one or more cheque templates is selected based on metadata associated with the cheque image. One or more zones of sensitive information associated with the cheque image are identified based on the one or more access privileges assigned to the user and a comparison with the selected cheque template. One or more characters are extracted from the one or more zones of sensitive information. The extracted one or more characters are aliased based on an aliasing rule. Another cheque image is generated by overlaying the one or more zones of sensitive information with the aliased one or more characters.
Abstract: The present invention provides a method and system for converting an XML artifact into a Topic Map instance. The method includes consolidating, by a schema consolidation module, an XML schema of the XML artifact; extracting, by an extracting module, a topic map model from the consolidated XML schema; and generating, by a converter, the topic map instance from the topic map model and the xml artifact.
Abstract: The present disclosure provides method for accessing digital web content. It provides for selective access rights for users, to a web content. When the user tries to retrieve the data, the system checks for the rights available to the user, and accordingly implements the access before providing the content.
March 19, 2015
Date of Patent:
August 6, 2019
Shikha Gupta, Ravi Sankar Veerubhotla, Ashutosh Saxena, Harigopal K. B. Ponnapalli