Abstract: An information processing apparatus includes: an output management information storage unit in which one or more pieces of output management information having an output condition, which is a condition for outputting emotion information and is a condition related to content, and emotion information are stored; an input information accepting unit that accepts input information that is content; an output information acquiring unit that judges whether or not information acquired using the content accepted by the input information accepting unit matches each of the one or more output conditions, and acquires emotion information that is paired with each of the one or more matching output conditions, from the output management information storage unit; and an information output unit that outputs the one or more pieces of emotion information acquired by the output information acquiring unit.

Abstract: An apparatus, method, and computer program product for the improved development of training data sets for use in connection with machine learning models capable of operating on natural language data records and other unstructured data in a network environment. Some example implementations provide for the generation and presentation of record images in a user interface that allows captures user actions reflecting higher-order data analysis and discernment for incorporation into training protocols used for machine learning models.

Abstract: A computing device includes a processor and a medium storing instructions. The instructions are executable by the processor to: receive a database query for an approximate aggregation of a numerical value of a plurality of records, wherein each record includes the numerical value and a filter value; in response to the database query, determine a count of records that have filter values within an importance threshold associated with the database query; and determine the approximate aggregation of the numerical value based on the count of records and the importance threshold associated with the database query.

Abstract: An approach for implementing function semantic based partition-wise SQL execution and partition pruning in a data processing system is provided. The system receives a query directed to a range-partitioned table and determines if operation key(s) of the query include(s) function(s) over the table partitioning key(s). If so, the system obtains a set of values corresponding to each partition by evaluating the function(s) on a low bound and/or a high bound table partitioning key value corresponding to the partition. The system may then compare the sets of values corresponding to different partitions and determine whether to aggregate results obtained by executing the query over the partitions based on the comparison. The system may also determine whether to prune any partitions from processing based on a set of correlations between the set of values for each partition and predicate(s) of the query including function(s) over the table partitioning key(s).

Abstract: A first data tree and a second data tree may be accessed. The first data tree may include a first set of directory nodes and a first set of file nodes, and the second data tree may include a second set of directory nodes and a second set of file nodes. The first data tree may be converted into a first data tree file, and the second data tree may be converted into a second data tree file. A delta for the first data tree and the second data tree may be generated based on a comparison of the first data tree file and the second data tree file.

Abstract: In some examples, an anomaly database system is provided for processing metrics in telemetry data. An example anomaly database system comprises a continuous data management (CDM) node, the CDM node including a metrics library for sending out system metrics in a sparse manner and a statistics relay for receiving streaming metrics from nodes in a node cluster, the node cluster including the CDM node, the statistics relay pushing the received metrics to a metrics collector. A sparse consumers module pulls metrics, from the metrics collector, pushed to the metrics collector by the statistics relay.

Abstract: The disclosure provides for isolation of concurrent read and write transactions on the same file, thereby enabling higher file system throughput relative to serial-only transactions. Race conditions and lock contentions in multi-writer scenarios are avoided in file stat (metadata) updates by the use of an aggregator to merge updates of committed transactions to maintain file stat truth, and an upgrade lock that enforces atomicity of file stat access, even while still permitting multiple processes to concurrently read from and/or write to the file data. The disclosure is applicable to generic file systems, whether native or virtualized, and may be used, for example, to speed access to database files that require prolonged input/output (I/O) transaction time periods.

Abstract: In one aspect, a data accumulation apparatus includes a script execution environment, an accumulation and retrieval unit accumulating data and performing retrieval on the accumulated data, a notification unit outputting notification in response to that data newly accumulated in the accumulation and retrieval unit matches one of conditions registered in advance, and a storage unit storing scripts and action correspondence information. The script execution environment has property of being capable of describing an instruction to perform data retrieval and an instruction to perform communication through the network, according to a script being executed.

Abstract: The present technology relates to identifying one of a plurality of artificial intelligence models based on a received key value. The received key value is applied to the identified one of the artificial intelligence models which is trained to output one of a plurality of actual index values. The one of the actual index values is compared to a range within the actual index values to determine when the one of the actual index value points to the data block. A received input-output operation is performed on the data block when the one of the actual index values is determined to point to the data block.

Abstract: A data store item count process determines the number of items in a data store (e.g., the number of items in a database table). In response to receipt of triggering events (e.g., additions or deletions of items in a table), a function registered to process the events is launched. The function processes the events to identify a net change to a count of items, and updates a value in a data store based on the net change. Multiple functions may process events for respective sets of partitions of a table, or for respective sets of tables, and update a distinct count value for each partition or table. In some instances, the process is performed within the context of a serverless compute environment; the function may retire, without saving an execution state for the function. A reporting function may access the value and send the value to a metrics reporting service.

Abstract: A query-set is used to obtain recommendation results from different recommendation algorithms available locally on a device. The same query-set is used to obtain recommendation results from a remote, well-established online recommendation system using an unknown recommendation algorithm. Distances are measured between the recommendation results from the online recommendation system and the recommendation results from each of the local recommendation algorithms. The local recommendation algorithm having generated recommendation results with a smallest distance to the recommendation results from the online recommendation system is selected for generation of recommendations based on a local recommendation algorithm.

Abstract: A technique produces a graph data structure based on at least partially unstructured information dispersed over web documents. The technique involves applying a machine-trained model to a set of documents (or, more generally “document units”) to identify topics in the documents. The technique then generates count information by counting the occurrences of the single topics and co-occurrences of parings of topics in the documents. The technique generates conditional probability information based on the count information. An instance of conditional probability information describes a probability that a first topic will occur, given an appearance of a second topic, and a probability that the second topic will occur, given an appearance of the first topic. The technique then formulates the conditional probability information in a graph data structure. The technique also provides an application system that utilizes the graph data structure to provide any kind of computer-implemented service to a user.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer-storage medium, for using a search engine implemented on a user device to identify topics or tasks associated with native application content. The method may include actions of receiving a set of data that is generated by the native application and that includes (i) native application content, and (ii) context information associated with the native application content, indexing the data on the user device, and then identifying one or more tasks based on the indexed data.

Abstract: Policy-based performance of storage management operations on objects of a file system using an index of the file system is presented herein. An object policy component maintains an object policy specifying that an operation is to be performed on an object of objects that have been stored in a system in response to a determination that a state of the object satisfies a defined policy condition. Further, a job component periodically accesses an index data structure of the system comprising respective attributes of the objects that have been stored in the system, and in response to the state of the object being determined, based on a group of attributes of the respective attributes of the object, to satisfy the defined policy condition, performs the operation on the object.

Abstract: Described is a system that provides deduplication management at a virtualization layer allowing virtual machines to store deduplicated data amongst various back-end data storage architectures. For example, the system may be storage-agnostic by operating at a hypervisor layer to fully leverage the benefits provided by virtualization. Accordingly, implementing deduplication by a hypervisor results in “pluggable” software-defined storage management. In addition, such a system may be implemented on any on-demand infrastructure (e.g. Infrastructure as a Service (IaaS)) environment that includes varying types of back-end storage solutions including solutions from various vendors. In addition, by operating within the virtualized layer of an on-demand computing resource environment (e.g. cloud environment), the system may provide deduplication across different resource clusters (e.g. hypervisor clusters) and environments.

Abstract: Various embodiments relate generally to data science and data analysis, and computer software and systems, 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 user interfaces may be implemented as computerized tools for presenting summarization of dataset attributes to facilitate discovery, formation, and analysis of interrelated collaborative datasets. In some examples, a method may include receiving data resulting from insight calculations. Insight calculations may be based on a derived dataset attribute. Also, the method may include presenting a data arrangement overview summarizing the data attributes as an aggregation of data attributes in a portion of the user interface.

Abstract: A method, system and computer program product for classifying a data collection of data of a predefined domain. A hierarchical representation scheme describing terms of the domain and one or more relationships between the terms is provided. At least one classifier may be applied on the data collection, resulting in a set of term assignments. Each term assignment of the term assignments associates a term candidate with a respective confidence value to the collection or to one or more data items of the collection. At least one of the term assignments may be refined based on the representation scheme and the set of term assignments.

Abstract: Disclosed is a method of managing a network of field-specific entity records. The method comprises accessing the network of field-specific entity records comprising at least one pair of field-specific entity records within at least one field segment, wherein the at least one pair of field-specific entity records is associated with relations therebetween, and wherein the at least one pair of field-specific entity records comprises a first pair of field-specific entity records and at least one second pair of field-specific entity records; determining a weightage score of each of the relations between the at least one pair of field-specific entity records; determining an importance score of each field-specific entity record; determining a change in the importance score, and/or the weightage score of a relation between field-specific entity records of the at least one second pair of field-specific entity records; and updating the network of field-specific entity records.

Abstract: 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 one or more computerized tools may be configured to discover, form, and analyze, for example, via one or more layered data files, interrelations among a system of networked collaborative datasets. In some examples, a method may include transforming of a set of data to an atomized format to form an atomized dataset that includes a derived dataset attribute. The method may also include presenting data representing an annotation at the user interface based on the derived dataset attribute. In some examples, the annotation may be associated with a layer file.

Abstract: 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 one or more computerized tools may be configured to discover, form, and analyze, for example, via one or more layered data files, interrelations among a system of networked collaborative datasets. In some examples, a method may include transforming of a set of data to an atomized format to form an atomized dataset that includes a derived dataset attribute. The method may also include presenting data representing an annotation at the user interface based on the derived dataset attribute. In some examples, the annotation may be associated with a layer file.