Abstract: Disclosed are systems and methods that automate the process of analyzing interactive content data using artificial intelligence and natural language processing technology to generate subject matter identifiers and sentiment identifiers that characterize the interaction represented by the content data. The automated processing classifies, reduces, segments, and filters content data to accurately, automatically, and efficiently characterize the content data. The results of the analysis in turn allow for identification of system and service problems and the implementation of system enhancements.

Abstract: A data management system includes: a transceiver; a memory; and a processor communicatively coupled to the transceiver and the memory and configured to: receive, via the transceiver, a copy data request for unstructured data; access, via the transceiver in response to the copy data request, a plurality of backed-up files of unstructured data stored in a first data storage device; send, in response to the copy data request, a plurality of Virtual Data Files (VDFs) to a second data storage device, the processor being configured to respond to receipt of information from each of the plurality of VDFs to retrieve a respective backed-up file of unstructured data of the plurality of backed-up files of unstructured data stored in the first data storage device.

Abstract: At least some embodiments are directed to a system to compute uniform structured summarization of customer chats. In at least some embodiments, the system may operate a processor and receive a corpus of chats between customers and customer service representatives of an enterprise. Grouping the corpus of chats into subgroup task types and then extracting chat keywords and chat related words for each subgroup task type. Generating an expandable template data structure for each subgroup task type. Processing at least one chat to extract chat utterances and chat snippets ranking the chat utterances and chat snippets. Populating the expandable template data structure based on rankings to generate a chat summary data structure.

Abstract: A method for performing data transfer includes: obtaining source data; populating a staging table with the source data; making a first determination that the source data was successfully populated to the staging table; making a second determination that a target table is available, in which an application is directed to use data in the target table; and initiating, based on the first determination and the second determination, a data source switch of the application, in which the data source switch directs the application to use the source data in the staging table and not use the data in the target table, in which the application uses the source data in the staging table when the data source switch is successful.

Abstract: Methods, systems, and computer program products for de-duplicating data in executable files in a container image are disclosed. The method may include receiving a request to read a file in a first layer in a container image including a plurality of layers, wherein the file is a delta file which is from an updated executable file based on a base executable file, the base executable file is in a lower layer than the first layer in the container image, and the delta file includes block mappings between the updated executable file and the base executable file and different data between the two files, and blocks included in the two files are based on respective file structure. The method may also include restoring the updated executable file based on the delta file and the base executable file. The method may further include returning data in the updated executable file.

Abstract: Technologies for grouping images, and ranking the images and the groupings, based on entities shown in the images. Images may be grouped based on faces shown in the images. Different images with faces that indicate the same entity (e.g., Adam) may be automatically grouped together. Different images with faces that indicate the same multiple entities (e.g., the people in my family) may also be automatically grouped together. Such automatic grouping may be based on facial recognition technologies. Further, images and groups of images may be automatically ranked based on the faces shown and entities represented. Such rankings may also be influenced by adjacent data that indicates family and friends and the like, and that can be used to identify such entities in the images.

Abstract: Methods, systems, and apparatuses for audience metric determination are described herein. An audience segment may be targeted for delivery of content. A clustering algorithm may be used to categorize a quantity of users or devices into subsets based on a propensity to consume, present or output a particular type of content, and a quantity of time to output the particular type of content. A weight may be assigned to each subset based on its relevance to other subsets, such as based on data variance, e.g., on a distance to a midpoint of a specific subset of the subsets. An index parameter may be determined for the datasets, e.g., based on each weight for each subset, and data may be generated that reflects a ranking of content delivery spots for delivery of content to the audience segment.

Abstract: In a dual node system, each node can store metadata updates in a volatile memory metadata log. Metadata pages can be used to access data stored on a volume. A node designated as preferred or affined for a volume can be expected to receive I/Os directed to the volume. A preferred node for a volume can record, in its volatile memory metadata log, the metadata changes for the metadata pages used to access data stored on the volume. A non-preferred or non-affined node for the volume can infrequently receive I/Os directed to the volume. A non-preferred node for a volume can record, in its volatile memory metadata log, pointers or references to the metadata changes for the metadata pages used to access data stored on the volume, where the pointers or references map to persisted copies of the meta changes as stored in a persisted metadata log.

Abstract: Systems and methods for parsing a software component search query to enable multi entity searches are provided.

Abstract: Data is collected from a set of devices according to a data collection policy. The data is associated with at least one of: device configuration, device state, or device behavior. A norm is established using the collected data. A different data collection policy is established based on the norm. Data is collected from a particular device according to the different data collection policy. The norm is compared to the data collected from the particular device. If there is a deviation beyond a threshold deviation between the norm and the data collected from the particular device, a responsive action is taken.

Abstract: A method is for determining a further data block. An embodiment of the method includes receiving a further timestamp transaction via a first interface, including a hash of a dataset and a further verification time; receiving a distributed ledger via the first interface, including data blocks; determining via a first computation unit, a first time by querying a time server; performing via the first computation unit, a first check based on the first time and the further verification time; and determining via the first computation unit, upon first check being positive, the further data block based on the distributed ledger, the further data block including the further timestamp transaction. A block creation system is also included in another embodiment, for determining a further data block, the system including a first interface and first computation unit.

Abstract: Case management systems and techniques are disclosed. In various embodiments, an indication to create a case instance is received. A case model definition is parsed to determine a hierarchical data model to be used to create the case instance and a placeholder data to be associated with a case node comprising the hierarchical data model. The case model definition is used to create the case instance, including by associating the placeholder data with the case node in the case instance as created.

Abstract: Resource lock ownership identification is provided across processes and systems of a clustered computing environment by a method which includes saving by a process, based on a user acquiring a resource lock, a lock information record to a shared data structure of the clustered computing environment. The lock information record includes user identification data identifying the user-owner of the resource lock acquired on a system executing the process. The method also includes referencing, by another process, the lock information record of the shared data structure to ascertain the user identification data identifying the user-owner of the resource lock, and thereby facilitate processing within the clustered computing environment.

Abstract: A graph-based data cataloging system, product and method that structures expert knowledge and statistically driven data analytics into a system-based framework for finding and relating enhanced metadata on subject-relevant, curated datasets from disparate, externally held data sources is shown. Displayed across a knowledge graph of nodes of datasets linked by their metadata attributes, the system simplifies the search and retrieval of multiple datasets of relevance to a user's technical, content, and resource-driven needs.

Abstract: An event processing system comprising a processor and a non-transitory computer readable medium coupled to the processor. The non-transitory computer readable medium stores computer-readable code executable to provide a domain-agnostic service for analyzing data and processing heterogeneous events conforming to a plurality of schemas using the service. The domain-agnostic service comprises an adaptive data model and an adaptive processing model. The adaptive data model supports runtime event type discovery and event schema management that reacts to new schemas discovered at runtime. The adaptive processing model supports configurable partitioning of events by event type and time and is reactive to create new aggregations and analyses based on the propagation of new partitions.

Abstract: The present disclosure relates to generating a complex entity index based on a combination of atomic and deep learned attributes associated with instances of a complex entity. For example, systems described herein generate a multi-dimensional representation of entity instances based on evaluation of digital content associated with the respective entity instances. Systems described herein further generate an index representation in which similarity of entity instances are illustrated and presented via an interactive presentation that enables a user to traverse instances of an entity to observe similarities and differences between instances of an entity that have similar embeddings to one another within a multi-dimensional index space.

Abstract: A system and method for content management, may include receiving content created by a creator; creating a container to contain the created content and storing the created content in the container; determining a content type for the content; based on the determined content type, identifying items of metadata specified for the content type (name metadata; support data; corresponding; determining whether an identified item of specified metadata corresponding to the content is missing from the container; and prompting a user to supply identified missing metadata corresponding to the container.

Abstract: Some embodiments provide a non-transitory machine-readable medium that stores a program. The program receives a plurality of documents. The program further uses a visual model to generate a vector representation for each document in the plurality of documents. The program also clusters the plurality of documents into a set of clusters based on the vector representations of the plurality of documents. The program further determines a sample set of documents from the plurality of documents based on the set of clusters.

Abstract: In accordance with some aspects of the present disclosure, a non-transitory computer readable medium is disclosed. The non-transitory computer readable medium includes instructions when executed by a processor cause the processor to write an object to an object store using an object-based access protocol, look up the object from the object store using a file-based access protocol, and create one or more directories on-demand in the object store.

Abstract: To efficiency search for an object associated with a sensed event, an information processing apparatus includes a sensor that analyzes a captured video and senses whether a predetermined event has occurred, a determining unit that determines a type of an object to be used as query information based on a type of the event in response to sensing of the event occurrence, and a generator that detects the object of the determined type from the video and generates the query information based on the detected object.