Abstract: In an exemplary embodiment, an application server is disclosed that receives user information including textual content from a user device. The application server improves electronic communications and user collaboration by searching public or private databases for information relevant to the received textual information and providing a means for including selected related information such as links with an electronic communication or document when it is sent to a recipient. The application server interfaces with text messaging, instant messaging, email, and document applications to improve the information accuracy and efficiency of generating a document or message as well as improving the ease of communication and collaboration.

Abstract: A system employing new and improved artificially intelligent system for employing modularized and taxonomy-based classifications to generate compliance-related content. In one embodiment, the system comprises monitoring circuitry that receives regulatory compliance data from one or more regulatory institutions, as well as a taxonomy engine that processes the regulatory compliance data to generate taxonomy-based classifications of the regulatory compliance data comprising a plurality of modules and compliance requirements within each module.

Abstract: A machine learning-based system and method for content clustering and content threat assessment includes generating embedding values for each piece of content of corpora of content data; implementing unsupervised machine learning models that: receive model input comprising the embeddings values of each piece of content of the corpora of content data; and predict distinct clusters of content data based on the embeddings values of the corpora of content data; assessing the distinct clusters of content data; associating metadata with each piece of content defining a member in each of the distinct clusters of content data based on the assessment, wherein the associating the metadata includes attributing to each piece of content within the clusters of content data a classification label of one of digital abuse/digital fraud and not digital abuse/digital fraud; and identifying members or content clusters having digital fraud/digital abuse based on querying the distinct clusters of content data.

Abstract: An example operation may include one or more of creating, by a blockchain user of a blockchain network, a world state checkpoint transaction requesting world state validation, endorsing, by one or more endorser nodes or peers, the world state checkpoint transaction, transferring endorsements to the blockchain user, recording, by an orderer node or peer, the endorsed world state checkpoint transaction into a block, validating and committing all transactions in the block, calculating and signing a hash of a current world state, by all blockchain nodes or peers of the blockchain network, and verifying, by the blockchain user, world state integrity from the calculated and signed hashes of the current world state.

Abstract: Systems and methods are described for responding to a search query with a contextually relevant voice output. An illustrative method receives a search query, determines an answer to the search query, identifies a media content reference included in the search query, determines, based on the media content reference, a personality associated with the media content reference, identifies a voice profile of the personality, and generates audio output using the voice profile of the personality, the audio output including the answer to the search query.

Abstract: A system for executing a streaming query includes an interface and a processor. The interface is configured to receive a logical query plan. The processor is configured to determine a physical query plan based at least in part on the logical query plan. The physical query plan comprises an ordered set of operators. Each operator of the ordered set of operators comprises an operator input mode and an operator output mode. The processor is further configured to execute the physical query plan using the operator input mode and the operator output mode for each operator of the query.

Abstract: A method performed by a block-storage server, of storing data is described. The method includes (1) receiving, from a remote file server, data blocks to be written to persistent block storage managed by the block-storage server; (2) receiving, from the remote file server, metadata describing a placement of the data blocks in a filesystem managed by the remote file server; and (3) organizing the data blocks within the persistent block storage based, at least in part, on the received metadata. An apparatus, system, and computer program product for performing a similar method are also provided.

Abstract: Embodiments provide for a primary storage array having multiple storage tiers. The multiple storage tiers include one or more performance tiers and at least one deduplicated storage tier storing deduplicated data. One embodiment provides for a data storage system including the storage array and an I/O engine to manage I/O requests for the storage array. The data storage system additionally includes a virtual execution environment to execute a virtual backup engine, the virtual backup engine to generate backup data for the one or more storage tiers of primary storage and deduplicate the backup data and a resource manager to manage a resource allocation to the virtual backup engine based on a hint received from the virtual backup engine, the hint associated with a backup operation that has a characterization selected from a set including computationally intensive and I/O intensive.

Abstract: Described are techniques for anomaly detection including a method comprising sorting a univariate data set in an numeric order and generating a second univariate data set based on the sorted univariate data set, where respective elements in the second univariate data set correspond to respective differences between consecutive elements in the sorted univariate data set. The method further comprises sorting the second univariate data set in numeric order and generating a third univariate data set that includes index values corresponding to respective differences in the sorted second univariate data set that are above a threshold. The method further comprises modifying the third univariate data set and defining a set of clusters based on the modified third univariate data set. The method further comprises clustering the sorted univariate data set according to the set of clusters and characterizing a new data point as anomalous in response to the clustering.

Abstract: Techniques and apparatus for dynamic data access mode processes are described. In one embodiment, for example, an apparatus may a processor, at least one memory coupled to the processor, the at least one memory comprising an indication of a database and instructions, the instructions, when executed by the processor, to cause the processor to determine a database utilization value for a database, perform a comparison of the database utilization value to at least one utilization threshold, and set an active data access mode to one of a low-utilization data access mode or a high-utilization data access mode based on the comparison. Other embodiments are described.

Abstract: A connected device at a client network implements a local data classification service for classifying data based on a data classification service of a remote provider network. The local data classification service receives a request to classify data at one or more data sources of the client network. The request is initiated from a client device of the client network according to a management interface for a data classification service of a remote provider network (e.g., using the same API request used by the remote classification service). The local data classification service obtains at least some of the data from the one or more data sources of the client network. The local data classification service classifies the obtained data according to different types of sensitivity using the data classification engine in the execution environment without the data being exposed outside of a data isolation boundary of the client network.

Abstract: A method of augmenting an information retrieval method including receiving a query, parsing the query to generate an instance graph, providing a plurality of constraint graphs, organized into at least two ranks, each constraint graph associated with a focus, determining at least one of the constraint graphs matching a structure of the instance graph, and annotating the query with the focus of each matching constraint graph of a highest rank among all matching constraint graphs.

Abstract: An example operation may include one or more processing transactions of a plurality of blocks of a blockchain of the blockchain network to determine a user of a plurality of users that is a party of the respective transaction and a mining pool of one or more mining pools that included the respective transaction in the blockchain, performing a statistical analysis of the transactions to determine if the transactions of a user of the plurality of users is distributed across the one or more mining pools in a statistically expected manner, determining that the user has a special relationship with one or more of the one or more mining pools if the transactions of the user are not distributed across the mining pools in a statistically expected manner, and for a user that is determined to have a special relationship, determining one or more of the mining pools with which the determined user has a special relationship.

Abstract: The present disclosure relates to a method for collecting data from a number of vehicles, in which at least one data collection device of a respective vehicle can be configured to read, store and transmit information recorded by respective vehicle sensors to a server. The at least one data collection device of a respective vehicle can also be configured by means of a control command to generate and transmit to a server a data set using selected values from a number of selected vehicle sensors, and in which the control command is generated by a central control device and is transmitted to the at least one data collection device.

Abstract: Apparatuses, methods, systems, and program products are disclosed for cluster configuration backup and recovery. One method includes receiving, by use of a processor, configuration data for a cluster. The method includes storing the configuration data for the cluster. The method also includes forming a machine-readable code that corresponds to the stored configuration data for the cluster. The machine-readable code may be used for restoring the stored configuration data to the cluster.

Abstract: A system and method for generating automatic false positive estimations for website matching is described. Several sets of assets and Uniform Resource Locators (URLs) are aggregated. Each of the several sets of assets is searched across webpage content corresponding to the several URLs to determine matches between the sets of assets and webpage content. One or more false positive estimations is determined, where each of the one or more false positive estimations corresponds to the one or more matches. A combined score is generated based on the one or more false positive estimations.

Abstract: Systems and methods that allow examination of response data collected from content providers and provide for classification and routing according to the classification. The process of classification employs an unsupervised, or partially unsupervised, Machine Learning classifier model for identifying data collection responses that contains no data, mangled data, or a block, for assigning a classification correspondingly and for feeding the classification decision back to a data collection platform.

Abstract: Examples of dynamic database query efficiency improvement are provided herein. Query portions of a received database query can be identified as candidates for replacement. The candidates for replacement can be query portions that reduce the efficiency of the query. Alternative queries can be determined that include substitute query portion(s) in place of candidate(s) for replacement. An expected performance of the alternative queries can be determined. Based at least in part on the expected performance of the alternative queries, one or more alternative queries can be selected as replacement database queries for the received database query.

Abstract: Adaptable internet-of-things (IoT) computing systems and methods are disclosed for improved and flexible declarative control of streaming data, such as Big Data, in compute intense environments. A declarative scripting engine determines an input data stream based on a first declarative statement defining input data stream variable(s) of a declarative scripting language in declarative scripting module(s). The input data stream is bound to a stream controller and is ingested into computer memory. The declarative scripting engine generates a snapshot data stream based on a second declarative statement in the declarative scripting module(s), and is derived from the input data stream. A stream model is defined, where a listener entity comprising an event is triggered based on the input data stream or the snapshot data stream as ingested into the stream model.

Abstract: A computer-implemented method includes positioning a sliding window over a string of data and calculating a hash value using a rolling hash function for data encompassed by the sliding window. The method includes determining whether the calculated hash value for the data encompassed by the sliding window matches the value of an element in a cut point candidate (CPC) array by comparing the calculated hash value to the value of a first element in the CPC array. In response to the calculated hash value being equal to the value of the first element in the CPC array, the method includes defining an index of the sliding window as the cutting point for a data block.