Abstract: A modified configuration management database (CMDB) system is disclosed in which detected configuration item (CI) vulnerabilities are stored as less-resource-intensive detection objects, rather than as more-resource-intensive vulnerable item (VI) objects. The system includes a vulnerability response (VR) server that enables promotion rules to be created and periodically applied to the stored detections. When the conditions of a detection promotion rule are satisfied by information relating to a stored detection, a new VI may be created and related to the stored detection within the CMDB. The disclosed promotion rules can be configured to ensure that VIs are only automatically created for high-risk or relevant detections, substantially reducing the number of VIs to be created, stored, and managed. As such, the disclosed system substantially reduces resource consumption and improves the efficiency and operation of the CMDB.

Abstract: Methods and systems described herein are directed to aggregating and querying log messages. Methods and systems determine event types of log message generated by event sources of the distributed computing system. The event types are aggregated into aggregated records for a shortest time unit and event types are aggregated into aggregated records for longer time units based on the aggregated records associated with the shortest time unit. In response to a query regarding occurrences of an event type in a query time interval, the query time interval is split into subintervals with time lengths that range from the shortest time unit to a longest time unit that lie within the query time interval. The method determines a total event count of occurrences of the event type in the query time interval based on the aggregated records with time stamps in the subintervals. The event count in the query time interval may be used to detect abnormal behavior of the event sources.

Abstract: A quantum file attribute service is disclosed. A quantum computing system receives a file metadata command requesting quantum file metadata. It is determined that a quantum file is encompassed by the file metadata command, the quantum file comprising a qubit. Quantum file metadata that identifies information about the quantum file is accessed. The quantum file metadata includes a qubit identifier that identifies the qubit. The quantum file metadata is sent to a destination.

Abstract: Techniques for fully or comprehensively resolving relationships within and among different data sets are disclosed. The techniques evaluate identification tags of respective transaction records to resolve transitive relationships between and among the identification tags, which vary across the different data sets. Based on this resolving, the techniques comprehensively sort the identification tags into mutually exclusive sets of related identification tags. Additionally, the techniques resolve and sort identification tags that are transitively unrelated to every other identification tag. At least these features enable comprehensive identification and intelligent sorting of related/unrelated transaction records, provide enhanced transaction tracking and security, more efficient and accurate transaction record storage (and in particular, of composite records), and enhanced tracking accuracy of accounts or types of units) as compared to known techniques.

Abstract: A system and method prioritizes and presents heterogenous medical data. The method includes retrieving medical data of a patient, the medical data including data from multiple data sources. The method includes phenotyping the medical data to generate a reasoning trail and reasoning outcome including one or more codes, the reasoning trail including a basis for which the reasoning outcome is determined. The method includes assigning a relevance score to each of the one or more codes. The method includes ranking the codes based on the relevance score of each of the one or more codes. The method includes displaying the codes in rank order.

Abstract: Provided by the present disclosure is a new category tag mining method, involving the field of knowledge graph technology, and including: obtaining a plurality of queries during a current preset time period; labeling a category tag on each query of the plurality of queries, by using a pre-trained sequence labeling model, to extract the category tag currently corresponding to the query from the query; and removing a category tag already existing in a preset current category tag library from category tags currently corresponding to all the queries, and determining a remaining category tag as a new category tag. The present disclosure also provides an electronic device and a non-transitory computer-readable storage medium.

Abstract: An information processing method is disclosed. The method includes: obtaining initial feature information of to-be-queried information; performing feature processing on the initial feature information of the to-be-queried information, to obtain target feature information of the to-be-queried information, where the feature processing includes at least feature dimension processing used to process a data dimension of the initial feature information of the to-be-queried information to be a preset dimension; performing a first retrieval operation on m pieces of candidate information based on the target feature information of the to-be-queried information, to obtain a first retrieval result; and performing a second retrieval operation on the first retrieval result based on the initial feature information of the to-be-queried information, to obtain result information corresponding to the to-be-queried information. The method can quickly and efficiently implement information retrieval.

Abstract: A computer provides a search interface that accesses multiple search providers, and aggregates their suggestions, providing a single, unified suggestion view across the multiple search providers. Suggestions are received from the multiple sources, such as a search engine on the internet or other public resource, and a search tool on the computer that accesses local or private resources. The suggestions are combined, ranked and displayed as a list to the user, from which the user is able to select.

Abstract: A system (400) configured to generate an expanded query for an electronic health database, the system comprising: a user interface (410) configured to receive a query comprising a search string and information about a clinical context in which the search is being performed; and a processor (460) comprising: (i) a model creation module (420) configured to generate a clinical information model comprising one or more clinical concepts; (ii) a prioritization module (430) configured to prioritize the one or more clinical concepts identified in the generated clinical information model based on the received information about the clinical context in which the search is being performed and a clinical guideline or management plan for the patient; (iii) a query expansion module (440) configured to create an expanded query using the prioritized clinical concepts; and (iv) a query module (450) configured to query the electronic health database using the expanded query.

Abstract: Methods, systems, and devices for generating a query using training observations are described. According to the techniques described herein, a device (e.g., an application server) may receive a set of queries including a set of fields in a tenant-specific dataset associated with the query. The device may generate a set of training observations for the queries based on the set of fields. The device then trains a first machine learning model to determine grouping hierarchies and a second machine learning model to determine aggregation predictions. The device then builds a combined machine learning model based on the determined grouping hierarchies and the aggregation predictions. According to techniques described herein, the device uses the determined grouping hierarchies and the aggregation predictions to rank a set of suggested queries determined in response to an input query and selects a suggested query for display based on the ranking.

Abstract: Creating an object is disclosed. An instance of a sharable type is created. An instance of a lightweight type is created. The sharable type is designated as a parent of the lightweight type. The instance of the sharable type is designated as a parent of the instance of the lightweight type. The instance of the sharable type is shareable by one or more other instances of the lightweight type.

Abstract: The present disclosure provides a search method, an electronic device and a storage medium, and belongs to a technical field of the Internet. The method includes: determining a first set of features corresponding to an original search statement by parsing the original search statement; obtaining each initial search result corresponding to the original search statement; determining a second set of features corresponding to an initial search result by parsing a title of the initial search result; determining a rewritten search statement corresponding to the original search statement and the initial search result by codecing the first set of features and the second set of features; and obtaining a supplementary search result corresponding to the rewritten search statement.

Abstract: There is provided a system and a method of generating an annotated structured dataset, comprising: receiving a medical classification term, searching over the unstructured patient data for extracting unclassified unstructured text fragments, presenting a subset of the unclassified unstructured text fragments, receiving an indication of a selection of none or at least one of the text fragments, and one of: (i) classifying non-selected unclassified unstructured text fragments according to the medical classification term, and classifying selected text fragments as not satisfying the medical classification term, and (ii) classifying selected unclassified unstructured text fragments according to the medical classification term, and classifying non-selected unclassified unstructured text fragments as not satisfying the medical classification term, and iterating the searching, and/or the presenting, until no text fragments are obtained by the search, wherein the annotated structured dataset is created by the classif

Abstract: Universal, automatic file conversion may be provided by a universal file conversion system or application. An input file may be received by the universal file conversion system. An input file type for the input file and a recipient of the input file may be determined. Programs available to the recipient for accessing a file may be determined. A target file type accessible to the recipient may be determined for converting the input file. A sequence of file conversions to convert the input file to the target file type may be determined. The input file may be converted to the target file type based on the sequence of file conversions. The converted file may be provided to the recipient. The recipient may return the converted file, and the converted file may be automatically converted back to the original input file type and provided to the original source of the input file.

Abstract: Methods and apparatus for conditional master election in a distributed database are described. A plurality of replicas of a database object are stored by a distributed database service. Some types of operations corresponding to client requests directed at the database object are to be coordinated by a master replica. Client access to the database object is enabled prior to election of a master replica. In response to a triggering condition, a particular replica is elected master. The master coordinates implementation of operations with one or more other replicas in response to client requests.

Abstract: Disclosed is a method for tracking an object, which is performed by a computing device including at least one processor, including: obtaining a query set including one or more query samples from a first frame included in an image sequence including two or more image frames; obtaining a detection set including one or more detection samples from a second frame included in the image sequence; and determining a label corresponding to each query sample included in the query set, based on the label of each detection sample included in the detection set.

Abstract: Embodiments for optimizing data storage instances in a cloud environment in which metadata is stored and accessed separately from content data in multiple different instances of data storage units. A metadata and content data storage instance optimization process determines the status of different instances of virtual storage resources for both metadata and content data. Full instances are powered down when they are not needed, empty instances are deleted, and data of partially full instances is moved to other appropriate instances to create empty instances that can be deleted. The data storage instance optimization process is provided as part of a data protection search process that provides an execution environment and user interface to the optimization process.

Abstract: A distributed computer system for delivering data to client-side application(s) is provided. The system includes a database configured to store immutable data blocks, a data distribution entity configured to split source-data into immutable data blocks and metadata. The data distribution entity is configured to replicate and store the data blocks on different storage nodes(s) of the database. The metadata comprises values referencing the data blocks for a key-value database call. The system further comprises a data fetching/delivering entity with a fuse-daemon configured to form a quorum read request for data block(s) out of a client-side request for a certain data range. The quorum-read request is a bundle of parallel requests to different storage nodes. The fuse-daemon is configured to fetch the data blocks delivered in the fastest response and to discard the rest. The fuse-daemon generates a virtual file comprising the corresponding range of data from the fetched data blocks.

Abstract: A method of distributed file deletion, performed by a storage system, is provided. The method includes receiving, at the storage system, a request to delete a directory and contents of the directory and adding the directory to a first set, listed in a memory in the storage system. The method includes operating on the first set, by examining each directory in the first set to identify subdirectories, adding each identified subdirectory to the first set as a directory, and adding each examined directory to a second set listed in the memory. The method includes deleting in a distributed manner across the storage system without concern for order, contents of directories, and the directories, listed in the second set.

Abstract: Aggregation of data and subsequent diving and/or grouping (i.e., slicing and dicing) of the aggregated data occurs by multi-stage parallel processing. Initially, multiple aggregation jobs are executed in parallel to aggregate data from a granular level to a higher level. Subsequently, query sets are executed in parallel for each of the aggregation jobs to divide and/or group the higher level data according to the queries and the segregated results are stored in a single table, which is partitioned for each aggregation job. Parallel processing of the query sets and storage in a single table is made possible by implementing a hybrid dynamic database schema, in which each table in the database includes one or more additional fields, each additional field comprising a set of dimension-dimension value pairs.