A disclosure range determination method includes accepting a disclosure range of data and metadata of the data, extracting attribute information of a user that belongs to the disclosure range of the data accepted in the accepting based on association information associating a disclosure range of data with attribute information of a user that belongs to the disclosure range, converting the metadata accepted in the accepting into a keyword based on association information associating a conversion rule that converts the metadata into significant information with a keyword corresponding to the conversion rule, and determining, by a computer, whether or not a user that belongs to the disclosure range accepted in the accepting qualifies for the disclosure range accepted in the accepting, based on whether or not the keyword converted in the converting is included in the attribute information extracted in the extracting.

A method and apparatus is disclosed herein for converting a virtual machine from an initial hypervisor format to a target hypervisor format utilizing deduplication metadata. The method may include generating a copy of a virtual machine by replication of deduplication metadata for one or more files corresponding to the virtual machine. Furthermore, the method may include opening the copy of the virtual machine from the replicated deduplication metadata. The method may also include converting the replicated deduplication metadata from an initial hypervisor format to a target hypervisor format to generate a converted virtual machine.

An information processing apparatus includes a processor configured to receive an operation performed by a user on an image associated with a designated file, and in response to the operation is an instruction related to an execution of a coordinated function, display a list of candidates for the coordinated function which is executable by using the designated file and display a list of files, which are different from the file, used for executing the coordinated function along with the designated file.

An embodiment of the present invention is directed to implementing machine learning to define business logic and lineage. The system analyzes data patterns of SORs as well as consumption attributes to define the business logic. An embodiment of the present invention may achieve over 95% match rate for complex attributes. When provided with thousands of SOR attributes, the innovative system may identify a handful of relevant SOR attributes required as well as the business logic to derive the consumption attribute.

Various embodiments relate generally to data science and data analysis, computer software and systems, and wired and wireless network communications to provide an interface between repositories of disparate datasets and computing machine-based entities that seek access to the datasets, and, more specifically, to a computing and data storage platform that facilitates consolidation of one or more datasets, whereby a collaborative data layer and associated logic facilitate, for example, efficient access to, and implementation of, collaborative datasets. In some examples, a method may include receiving a dataset having a data format into a dataset ingestion controller configured to form a collaborative dataset, interpreting data of the dataset against data classifications at an inference engine to derive at least an inferred attribute, associating the data with annotative data identifying the inferred attribute, and converting the dataset at a format converter to form an atomized dataset.

Various methods, apparatuses/systems, and media for automatically generating and/or updating corporate action swift (society for worldwide interbank financial telecommunication) messages are provided. A processor accesses a database that stores a plurality of static data sheets each including different type of static data; accesses a plurality of corporate action swift generator sheets each configured to link to the plurality of static data sheets from the database and generate a certain type of swift in an MT56x family of swift; implements a template that is linked to the plurality of corporate action swift generator sheets to access a desired static data sheet; automatically generates a corporate action MT56x family of swift message based on the template and the desired static data sheet; and automatically creates an MT56x swift file as output for the generated corporate action MT56x family of swift message in either a text file format or an excel file format.

Systems and methods for providing improved content previews of files stored in an online content management system with collaboration environment are disclosed. An optimized PDF rendering engine is used to reproduce the appearance of previewed PDF documents. The present disclosure includes a method of evaluating the available system tools for converting files from an existing format to a target format to determine the optimum tool(s) to use for the conversion process of a file.

Data transformation offloading in an artificial intelligence infrastructure that includes one or more storage systems and one or more graphical processing unit (‘GPU’) servers, including: storing, within the storage system, a dataset; identifying, in dependence upon one or more machine learning models to be executed on the GPU servers, one or more transformations to apply to the dataset; and generating, by the storage system in dependence upon the one or more transformations, a transformed dataset.

An information processing apparatus includes a controller configured to control notification of a function executable with contents of plural files when the plural files are acquired. In a further modification of the invention, when a first file included in the plural files is stored in a storage unit and a second file included in the plural files is acquired, the controller may control notification of a function that is executable with contents of the first and second files.

The present techniques generally relate to an apparatus for determining user progression data in a literary work, the apparatus comprising: a database comprising formatted literary data for two or more versions of a literary work; and circuitry to: process tracker position data for a first version of the one or more versions; and determine, from formatted literary data for the two or more versions, progression data for a second version of the literary work based on or in response to the tracker position data for the first version.