Abstract: Existing systems for document processing are either based on a supervised approach using annotated tags, and these systems identify section-based data from the unstructured documents without considering the statistical variations in content, which results in highly inaccurate content extraction. The disclosure herein generally relates to document processing, and, more particularly, to method and system for document indexing and retrieval. The system provides a mechanism to correlate unique words in a document with different topics identified in the document, based on a word pattern identified from the document. The correlations are captured in a knowledge graph, and can be further used in applications such as but not limited to document retrieval.

Abstract: This disclosure relates generally to adaptive learning based systems and methods for optimization of unsupervised clustering. The embodiments of present disclosure herein address unresolved problem of involving manual intervention in data preparation, annotating or labelling training data to train classifiers, and taking a number of clusters directly as an input from the users for data classification. The method of the present disclosure provides a fully unsupervised optimized approach for auto clustering of input data that automatically determines the number of clusters for the input data by leveraging concepts of graph theory and maximizing a cost function. The method of present disclosure is capable of handling a new data by continuously and incrementally improving the clusters. The method of present disclosure is domain agnostic, scalable, provides expected level of accuracy for real-world data, and helps in minimizing utilization of powerful processors leading to reduced overall cost.

Abstract: Existing systems for document processing are either based on a supervised approach using annotated tags, and these systems identify section-based data from the unstructured documents without considering the statistical variations in content, which results in highly inaccurate content extraction. The disclosure herein generally relates to document processing, and, more particularly, to method and system for document indexing and retrieval. The system provides a mechanism to correlate unique words in a document with different topics identified in the document, based on a word pattern identified from the document. The correlations are captured in a knowledge graph, and can be further used in applications such as but not limited to document retrieval.

Abstract: Disclosed are methods and systems that include receiving updated operating system information, encrypting the updated operating system information, and updating a map file. The updated operating system information is received at an encryption virtual machine. The encrypting the updated operating system information results in the encrypted updated operating system information. The encrypting the updated operating system information is managed by the encryption virtual machine. The updated operating system information is encrypted in response to receipt of the updated operating system information. The updated operating system information is encrypted using an encryption key.

Abstract: Various systems, methods, and processes to protect virtual machine data in cloud computing environments are disclosed. A request for application data is received. The application data is encrypted, the request is received at an encryption virtual machine, and the encryption virtual machine is configured to receive the request from application virtual machines via loaders. A map file is accessed to identify an application virtual machine for which the application data is requested and the application data is accessed in a storage volume. The storage volume is communicatively coupled to the encryption virtual machine, and the encryption virtual machine is coupled between the application virtual machines and the storage volume. The application data is received from the storage volume and decrypted at the encryption virtual machine. The decrypted application data is sent to the loaders.

Abstract: A computer-implemented method for automated delivery and identification of virtual drives may include (1) creating a drive-template archive that contains a collection of virtual-drive templates, each of which contains a unique burned-in configuration identifier, (2) receiving, a provision request to provision a virtual drive for a requesting virtual machine, (3) fulfilling the provision request by (A) creating a copy of an appropriate virtual-drive template that matches the specification of the provision request and (B) providing the copy of the appropriate virtual-drive template to the requesting virtual machine, and (4) utilizing, at the requesting virtual machine, the copy of the appropriate virtual-drive template in response to determining that the burned-in configuration identifier of the copy of the appropriate virtual-drive template corresponds to a drive configuration that fulfills the provision request. Various other methods, systems, and computer-readable media are also disclosed.

Abstract: Various systems, methods, and processes to protect virtual machine data in a cloud environment are disclosed. A request for requested data is received at an encryption virtual machine. The requested data is encrypted, and the encryption virtual machine is configured to receive the request from an application virtual machine via a loader. The requested data includes one or more operating system modules, and the operating system modules are configured to be used by the application virtual machine. The requested data is accessed in a storage volume, which is communicatively coupled to the encryption virtual machine. The requested data is then retrieved from the storage volume and decrypted at the encryption virtual machine. The decrypted data is then sent to the loader.

Abstract: A computer-implemented method for performing fast failovers may include 1) identifying an application to fail over from a first computing system to a second computing system, 2) identifying a first component of the application to fail over, the first component depending on a second component of the application and a third component of the application, the second component and third component being mutually independent, and 3) failing the application over from the first computing system to the second computing system by, based on a determination that the second component and third component are mutually independent, (i) taking the second component offline on the first computing system after taking the first component offline on the first computing system and (ii) taking the third component offline on the first computing system while bringing the second component online on the second computing system. Various other methods, systems, and computer-readable media are also disclosed.