Abstract: Disclosed is a system for determining contextually-relevant keywords related to text of an electronic document. The system comprises a memory, a database arrangement comprising an ontology and a synonym databank, a data processing arrangement and a sever arrangement. The data processing arrangement is operable to fetch the electronic document stored within the memory. Furthermore, the data processing arrangement determines the common words from the ontology and the synonyms corresponding to the common words from synonym databank. Moreover, the data processing arrangement determines the generated set of keywords comprising the common words and the synonyms. The server arrangement determines a preference score and an importance score for each keyword of the generated set of keywords. Furthermore, the server arrangement determines the cumulative rank of each keyword based on the preference score and the importance score, therefore determining contextually-relevant keywords.

Abstract: Instead of transferring a large original file, such as a virtual-machine image file, from a source system to a target system, the original file is encoded to define a recipe file that is transferred. The recipe is then decoded to yield a duplicate of the original file on the target system. Encoding involves identifying standard blocks in the original file and including standard-block identifiers for the standard blocks in the recipe in lieu of the original blocks. Decoding involves an exchange with a standard-block identifier server system, which provides standard blocks in response to received standard-block identifiers.

Abstract: Disclosed is a system for generating summary of at least one research document. The system comprising computing device associated with an entity, data repository comprising ontological database and synonym database and server arrangement communicably coupled via one or more data communication networks with the computing device and the data repository. The server arrangement is configured to acquire information included in at least one research document, analyze information using ontological database and synonym database to identify set of keywords corresponding to at least one research document, assign first score to each of the keywords based on document-centric property, assign second score to one or more relationships between the keywords based on relationship-centric property and generate summary for at least one research document.

Abstract: Described herein is a system and method for utilizing data flow analysis to perform data classification with respect to a source dataset and a generated derived dataset. A flow confidence for a field is calculated using an adaptive algorithm in accordance with the action performed and the derived dataset. An associated derived confidence for a particular tag is calculated in accordance with an associated confidence and the flow confidence. When the associated derived confidence is greater than or equal to a first threshold, the particular tag is copied to the derived dataset. In some embodiments, when the associated derived confidence is less than or equal to a second threshold, the particular tag is not copied to the derived dataset. Otherwise an action to be taken is identified. A response to the action is received and the adaptive algorithm is modified in accordance with the received response.

Abstract: A processing device determines that a parameter in a data store is associated with a parameter policy, wherein the parameter comprises a key-value pair and the parameter policy comprises metadata that affects a behavioral characteristic of the parameter. The processing device determines that a criterion included in the parameter policy is satisfied. The processing device determines one or more operations specified in the parameter policy and performs the one or more operations.

Abstract: A method includes setting a maximum total size of data saved in a snapshot area, creating a snapshot of a file system, including reference to a plurality of logical volumes, saving at least a part of the plurality of logical volumes in the snapshot area on condition that it does not exceed the maximum total size of data saved in the snapshot area, and executing copy-on-write processing in response to a writing request for data in the file system, the data not being saved in the snapshot area.

Abstract: Methods and apparatus are provided for filtering dynamically loadable namespaces (DLNs). An exemplary method comprises, in response to a job submitted by an application, obtaining a DLN portion of a global single namespace of a file system, wherein the DLN is associated with the job and is maintained in a capacity tier of a storage system; obtaining filtering directives from a user; reducing the DLN using a filtering mechanism on a directory tree associated with the DLN, based on the filtering directives, by removing files in the directory tree of the DLN that do not satisfy requirements of the filtering directives to generate a filtered DLN; and dynamically loading the filtered DLN, including reduced metadata for the filtered DLN relative to the DLN, from the capacity tier into a performance tier of the storage system for processing by the application.

Abstract: Example methods, non-transitory computer-readable medium, and systems for blockchain-based data processing are provided herein. In one example method, a blockchain network is identified, where the blockchain network includes a plurality of blocks. For each particular block of the plurality of blocks, a series of operations can be performed. An identifier of the particular block and an identifier of service data stored in the particular block are determined. A first mapping relationship is established between the determined identifier of the particular block and the determined identifier of the service data stored in the particular block. That first mapping relationship for the particular block is then stored in a relational database. In some instances, determining the identifier of the block includes obtaining digest information of the block, computing a value based on the digest information of the block, and associating the computed value as the identifier of the particular block.

Abstract: Methods, systems, and computer programs are presented for reclassifying content in an online service. One method includes an operation for classifying a content item, to be presented on an online service, as low-quality or approved. The method further includes an operation for storing, in a content database of the online service, the content item with a content certification record (CCR). The CCR includes a result of the classifying of the content item, a content classification platform signature (CCPS), and a content signature. Further, the method includes operations for detecting a trigger for determining if the content item has to be reclassified, and for checking if the item needs to be reclassified. The checking includes comparing the CCPS in the CCR to a latest CCPS and comparing the content signature in the CCR to a current content signature of the content item. The content item is reclassified based on the checking.

Abstract: A natural language processing system with pre-specified SQL queries is provided. A user input can be performed via a graphical user interface. The system can process via natural language processing, and return an intent field corresponding to one or more variables. Pre-specified SQL queries can be provided for possible intents. The query can be altered by populating with particular parameters. In addition, an answer can be returned to the user comprising natural language results and graphical material.

Abstract: A system selects multiple operators in a query graph by determining whether a corresponding value satisfies a threshold for each operator. The system sorts each selected operator in an ascending order based on a corresponding maximum thread capacity and determines an average number of threads of control based on available threads and the selected operators. The system allocates an initial number of threads to an initial selected operator in the ascending order, the initial number based on a minimum of the average number of threads and corresponding maximum thread capacity. The system determines a revised average number of threads based on remaining number of available threads and remaining number of the selected operators and allocates a next number of threads to a next selected operator in the ascending order, the next number based on a minimum of the revised average number of threads and corresponding maximum thread capacity.

Abstract: An approach is provided dynamically prioritizing question requests based on extracted question data. In the approach, performed by an information handling system, a number of question requests to a question and answering (QA) system are received from a computer network, and a plurality of question priority parameters are identified, including one or more question topics and a plurality question context parameters, by performing natural language processing (NLP) analysis of each question request. The approach determines a target priority value for each question request based on the plurality of question priority parameters identified for said question request. By evaluating the target priority values for the plurality of question requests, processing of the question requests is prioritized, such as by applying an artificial intelligence (AI) learned models and rule-based logic at the information handling system to evaluate the target priority values for the plurality of question requests.

Abstract: A non-transitory computer readable medium storing a program that causes a computer to execute a process, the process including obtaining text data, generating first index information indicating appearance positions in the text data for each of a plurality of characters or words obtained based on lexical analysis of the text data, generating second index information, the second index information being index information in which the appearance positions in the text data are aggregated for each character or word, specifying a data range in the first index information, to be referred in a pattern match search by using the second index information, and performing encoding for the text data based on the pattern match search by using the data range in the first index information.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for generating transaction associations in a waveform display. One of the methods includes receiving data representing a main signal for a selected transaction in a waveform display, the main signal including a plurality of main signal events. A search is performed for data representing one or more side signals associated with the main signal for the selected transaction, each side signal including a plurality of side signal events representing other transactions that are associated with the main signal at a time indicated by a corresponding main signal event. A visual indication is generated within the waveform display of an association between the selected transaction and one or more transactions identified by the one or more side signals associated with the main signal for the selected transaction.

Abstract: A method for parallel maintenance of data consistency includes: 1) a node broadcasts requests to other nodes in a network, request a synchronization data block of current synchronization cycle, and calculates a synchronization anchor of this synchronization cycle; 2) for node i requiring data feeding, writing the synchronization anchor of the current synchronization cycle in data block A0, and to produce an array [A]N based on the requirement; data block A0 is the provision that is be added into consistency data in the current synchronization cycle; 3) each node builds its own array [A]N in parallel and broadcasts the array; and 4) the node filters all received arrays of [A]N by the synchronization anchor of array, discards invalid data, and thereafter builds the synchronization data block for the next synchronization cycle.

Abstract: A method uses natural language for visual analysis of a dataset. The method displays a data visualization based on a first dataset. The method then extracts analytic phrases from a first natural language command related to the data visualization. The method computes conversation centers associated with the first natural language command based on the analytic phrases and computes analytical functions for the conversation centers, thereby creating functional phrases. The method updates the data visualization based on the functional phrases. The method extracts new analytic phrases from a second natural language command related to the updated data visualization and computes a temporary conversation centers associated with the second natural language command based on the new analytic phrases. The method derives new conversation centers from the original conversation centers and the temporary conversation centers using transitional rules.

Abstract: Systems, methods, and non-transitory computer-readable media (systems) are disclosed for generating meaningful and insightful user segment reports based on a high dimensional data space. In particular, in one or more embodiments, the disclosed systems utilize a relaxed bi-clustering model to automatically identify user segments in a data space including datasets of features specific to individual users. In at least one embodiment, the disclosed systems identify and include users in automatically generated user segments even though those users are associated with some, but perhaps not all, of the features as other members in the automatically generated user segments.

Abstract: A method uses natural language for visual analysis of a dataset. A data visualization is displayed based on a first dataset. The method then extracts analytic phrases from a natural language command related to the data visualization. The method computes conversation centers based on the analytic phrases and computes analytical functions associated with the conversation centers, thereby creating functional phrases. The method updates the data visualization according to the functional phrases. The method then extracts analytic phrases from a second natural language command related to the updated data visualization, and computes temporary conversation centers from these analytic phrases. The method then computes cohesion between the first analytic phrases and the second analytic phrases to build a set of conversation centers, and computes analytical functions from this set of conversation centers, thereby creating functional phrases.

Abstract: Techniques for identifying relevant, natural language documents within a data repository. An electronic document specifying natural language text describing an issue with a complex system is received. One or more portions are removed from the electronic document, where the portions are determined to satisfy one or more predefined filtering rules. A first set of terms are determined using a data dictionary structure, and a second set of terms are determined, where at least one term in the second set of terms satisfies at least one predefined pattern matching rule. A third set of terms are determined by processing the electronic document as an input to a machine learning model trained to recognize relevant terms within the electronic document. A synthesized electronic document is generated from the first, second and third sets of terms, and the synthesized electronic document is used to identify a set of relevant documents within the data repository.

Abstract: Mechanisms are provided to automatically identify source code relevant to a task among a set of disparate source code. The mechanisms search a plurality of working sets based on a given keyword associated with the task in order to identify a subset of working sets from a working set store that comprises the given keyword. The mechanisms identify source code files associated with the identified working sets. The mechanisms determine a score that depends on the occurrences of matched working sets for the given keyword within each identified source code file. For each directory or repository, the mechanisms determine an aggregated score for all the source code files comprised therein. The mechanisms present a listing of all identified source code files by directory and repository, where the listing illustrates a relevancy of repositories, directories, and source code files that comprise the given keyword associated with the task.