Abstract: A system identifies a data object, stored in a client, for replication. The system identifies a redundancy number associated with a protected amount of failed storage nodes. The system determines whether the total count of available storage nodes is at least two greater than the redundancy number. The system determines a distribution number that is at most the total count minus the redundancy number, in response to a determination that the total count of available storage nodes is at least two greater than the redundancy number. The system creates erasure code for the data object. The system allocates the distribution number of sections of a replica of the data object to a corresponding distribution number of available storage nodes and the redundancy number of sections of the erasure code to the redundancy number of available storage nodes, which excludes the corresponding distribution number of available storage nodes.

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: The present disclosure relates to searching for and committing low-frequency data to a database. An example method generally includes receiving, from a requesting application, a query for data from the data repository. A database system retrieves a set of indices associated with the data specified in the query from an index table in the data repository. Upon determining that the set of indices comprises a non-null set, the database system retrieves records associated with each index in the set of indices from a data table associated with the index table and returns the retrieved records to the requesting application.

Abstract: A system for performing continuous transaction log backups with minimal resource usage of the client computing devices that are processing the transactions is disclosed. The system detects at least one input/output (I/O) activity at a client computing device. The I/O activity can be associated with at least one database operation performed via the client computing device. The system then executes one or more native commands to backup transactions log data associated with the detected I/O activity to a virtualized location. Backing-up the transactions log data comprises dynamically identifying a mount path location corresponding to the virtualized location, and transferring the transactions log data to the dynamically identified mount path using the one or more native commands. The system can then perform data processing operations (for example, data chunking and deduplicating) on the transactions log data after it is received at the dynamically identified mount path location.

Abstract: Recommendation information is associated with an information classification label by a server of an online interaction platform, and a correspondence between the recommendation information and the information classification label is stored in a feature label database. The recommendation information associated with the information classification label is delivered to a user. Upon triggering of the recommendation information by a user, the information classification label associated with the recommendation information and an unique identifier associated with the user are obtained. By using the unique identifier, a user feature database is queried to determine whether a correspondence between the information classification label and the unique identifier has been established. If it is determining that the correspondence is not established, the correspondence between the information classification label and the unique identifier is established in the user feature database.

Abstract: With multiple software applications, multiple electronic devices for a user to access and work upon, and multiple potential storage locations for the files it is difficult for a user to remember the identity of a file worked upon, its storage location, or which application they employed. Whilst some applications provide a user with a listing of recently opened files these are only those accessed by that specific application upon a specific device. Embodiments of the invention provide users with a synthesized centralized view of all files accessed irrespective of where the user has stored the electronic content, with which electronic device the electronic content was accessed with, or with which software application the electronic content was accessed with.

Abstract: A DI recovery management system generates a plurality of ranked claimant records and recovery scores. A predictive machine learning model inputs disability income claim data and disability income claimant data into an event history model utilizing discrete-time survival analysis in conjunction with a gradient boosting machine learning model. The claim termination event is one of a plurality of preselected recovery events that indicate that a claimant has achieved return to work capacity. Claimant data used in modeling includes diagnosis data representative of workplace disability duration guidelines. The predictive machine learning model is continually trained using updated disability income claims data. The training procedure transforms claimant records extracted from a DI claims database into a longitudinal format that includes multiple person-year records corresponding to each claimant record.

Abstract: A taxonomy of categories, attributes, and values can be conflated with new data triplets by identifying one or more conflation candidates among the attribute-value pairs within a category of the taxonomy that matches the category of the data triplet, and determining a suitable merge action for conflating the data triplet with each conflation candidate. The task of determining merge actions may be cast as a classification problem, and may be solved by an ensemble classifier.

Abstract: A computer-implemented method of answering questions comprises: receiving, by one or more processors, a query; based on the query, generating, by the one or more processors, a matrix; based on the matrix, modifying, by the one or more processors, a dynamic memory; based on the matrix, determining, by the one or more processors, a first response from the dynamic memory; based on the matrix, determining, by the one or more processors, a second response from a database; based on the first response and the second response, determining, by the one or more processors, a third response; and in response to the query, providing, by the one or more processors, the third response.

Abstract: Methods and systems for generating search indexes in a virtual desktop environment are disclosed. An initial index generation module is configured to generate initial iterations of search indexes for a plurality of users associated with respective virtual desktops and store the initial iterations of search indexes on a shared data store. An incremental search indexing module is configured to update existing iterations of search indexes associated with the plurality of users according to respective schedules. A search processing module is configured to receive a search query from a first user while the first user is logged into the first virtual desktop, identify, utilizing an iteration of the search index associated with a first user and stored on the server storing search indexes for the plurality of users associated with respective virtual desktops, matching documents, and to cause search results corresponding to the matching documents to be presented via the first virtual desktop.

Abstract: An on-demand learning system provides an enhanced leaning environment capable of delivering relevant content on virtually any topic to specific learners. The learning system implements technical features that facilitate curation and subject matter validation of many different types of content. The technical architecture of the learning system also supports intelligent matching of learners to subject matter areas, creation of specific subject matter boards, and resilient maintenance of the boards.

Abstract: Systems and methods use a ZFS file system in a Windows-based computing environment without protocol conversion or native ZFS support on Windows-based computing devices. Windows-based computing devices may obtain native Windows-based access to data in a storage volume that is managed by a Unix-based storage management server executing a ZFS volume manager and file system. ZFS clones may be served as logical unit numbers to Windows-based computing devices. The ZFS nature of the accessed storage volume is unbeknownst to the Windows-based machines. This enables Windows-based utilities, applications, and tools executing on a Windows-based computing device to operate upon the data in ZFS-managed space the same as they might have operated on a workspace in an array-created hardware snapshot in the prior art. Users may use storage space from their Windows-based computing devices according to a Windows-based file system such as NTFS.

Abstract: In some aspects, an interconnectivity evaluation system identifies, in a data structure with data indicating links among entity data objects, first links between a first entity data object and additional entity data objects and second links between a second entity data object and the additional entity data objects. A connectivity score for the first and second entity data objects, which indicates a weight of a relationship between the first and second entity data objects, is computed based on the first links and the second links. Data in the data structure is modified to indicate a relationship between the first and second entity data objects. The relationship is associated with the computed connectivity score. If a difference between the connectivity score and a desired connectivity score exceeds a threshold, a recommendation is outputted to modify the connectivity score by changing at least some of the links among the entity data objects.

Abstract: Query service receives a query comprising at least a name component. The query service searches a document corpus to identify multiple passages, each comprising a mention of the name component within a selection of one or more documents of the document corpus. The query service collects bins, each bin comprising a distinct selection of the passages from the one or more documents, each of the bins identifying a separate relationship the name component participates in within the distinct selection of passages. The query service assesses a separate score of each respective bin reflecting the relevance of each respective bin to the query. The query service returns a response to the query with the bins each ranked according to each separate score.

Abstract: A system is provided, which may comprise: a word vector database configured to store word vectors, each of the word vectors representing a word or a phrase; a text database configured to store text data; and a processor configured to: receive a user input including a first term; obtain, for each word vector that is stored in the word vector database and that represents a word or a phrase other than the first term, a similarity between that word vector and a word vector representing the first term; select at least one second term based on the obtained similarity; perform a search in the text database using the at least one second term as a query for the search; and provide results of the search.

Abstract: Among other things, one or more techniques and/or systems are provided for location-aware content detection. In particular, content may be grouped into topic clusters (e.g., images, articles, and/or websites may be grouped into a football cluster, an earthquake cluster, etc.). A topic of a cluster may be assigned a global ranking (e.g., based upon an importance of a topic on a global scale) and/or local rankings for local regions (e.g., based upon importance of a topic to various local regions). A local ranking may be based upon user interaction with content associated with the topic (e.g., many users from Japan may be reading about the earthquake). In this way, content may be provided to users based upon global rankings and/or local rankings (e.g., content from around the world about the earthquake may be presented to users in Japan and/or other areas that have expressed interest in the earthquake).

Abstract: Provided are a method, an apparatus and an electronic device for determining a knowledge sample data set, the method includes: acquiring a preset number of SPO triplet formats and source texts; acquiring, according to the SPO triplet formats, n SPO entries corresponding to the SPO triplet formats; searching, in the source texts, m first texts that match the n SPO entries, and generating a first knowledge sample data set; determining k second texts that meet the SPO triplet formats from the m first texts and generating a second knowledge sample data set; generating a target knowledge sample data set according to the first knowledge sample data set and the second knowledge sample data set. In the embodiments, the knowledge sample data set is automatically generated, the volume generation speed is fast, the cost is low, and the data size that can be produced is large, thus meeting the training requirement.

Abstract: Techniques are provided for more efficient multi-row atomic, consistent, isolated and durable (ACID)-compliant transactions with snapshot isolation semantics (or just “multi-row transactions” for short). In some embodiments, the techniques are implemented in a computing system that includes a client application, a lightweight in-memory lease-based lock service, a multi-row transaction orchestrator, and an underlying database system. The transaction orchestrator implements a read protocol and a write protocol that provides support to the client application for carrying out multi-row transactions against the underlying database system irrespective of whether the database system itself supports multi-row transactions. The transaction orchestrator explicitly maintains transaction-level locks obtained from the lease-based lock service as part of the transaction protocol.

Abstract: Migrating content between enterprise content management systems is described. A source object identifier is identified for metadata tables for content for a source enterprise content management system, based on a migration job definition. The metadata tables are retrieved from the source enterprise content management system, based on the source object identifier. A target object identifier is identified for a target enterprise content management system, based on the metadata tables and the migration job definition. An object identifier map is created that maps the source object identifier to the target object identifier. The metadata tables are stored to the target enterprise content management system, based on the object identifier map. The content for the source enterprise content management system is retrieved. The content is stored as content for the target enterprise content management system.

Abstract: An adaptive link is generated for delivering a device platform-specific and personalized digital pass. When the adaptive link is activated by an end user, a network request is sent from an end-user device to a digital pass management system. The network request may include header information that identifies the device platform of the end-user device. The digital pass management system extracts query string parameters included in the adaptive link. Based on the parameters, a personalized data set in a specific data format such as JSON is generated. A template that is compatible to the device platform is selected. A digital pass that is compatible with the device platform is generated and delivered based on the requirements of the end-user device. In some cases, the adaptive link may include location information such as latitude and longitude coordinates. The digital pass generated may also be location specific.