Abstract: A system including one or more processors and one or more non-transitory computer-readable media storing computing instructions configured to run on the one or more processors and perform: bundling multiple registered queries of a dataset using a scheduling technique, wherein the dataset is homogenous in schema; running a single table scan of the dataset to process the multiple registered queries of the dataset in parallel; and generating a respective output responsive to each of the multiple registered queries. Other embodiments are disclosed.

Abstract: A method of identifying causal relationships includes receiving data comprising a set of values corresponding to one or more variables, and generating a list of candidate causal models of relationships between or within the variables. The list is ranked based on a likelihood of each candidate causal model, wherein the likelihood includes at least a correlation value. The method further includes receiving feedback identifying a candidate causal model and a change in rank of the candidate causal model, re-ranking the list based on the feedback, and displaying the re-ranked list. The method generates an intervention comprising a suggested modification corresponding to a variable of a selected causal model among the candidate causal models in the re-ranked list, receives additional data corresponding to the variable of the suggested modification and evaluates the additional data to determine whether the likelihood of the selected causal model has changed.

Abstract: A method for data processing and interactive information exchange with feature data extraction and bidirectional value evaluation for technology transfer is provided. During the process, a data processing instruction is formed after receiving a user operation instruction, and the corresponding data is obtained in accordance with the data processing instruction. Then, the corresponding data is processed to obtain specified data with feature data extraction; and the corresponding task for the specified data is being run to obtain a corresponding processing result, including a bidirectional value evaluation between the user and the processing result. A computer is also provided for use in connection with the method, where patent information is collected from the patent literature and subjected to processing, sorting, and analysis.

Abstract: An event query host can include an event processor configured to process an event stream indicating events that occurred on a computing device. The event processor can add representations of events to an event graph. If an event added to the event graph is a trigger event associated with a query, the event processor can also add an instance of the query to a query queue. The query queue can be sorted based on scheduled execution times of query instances. At a scheduled execution time of a query instance in the query queue, a query manager of the event query host can execute the query instance and attempt to find a corresponding pattern of one or more events in the event graph.

Abstract: A system and method include processing devices to implement an automated synchronization system for an intelligent talent platform, the automated synchronization system including one or more remote system adapters each coupled to a corresponding remote system, to retrieve one or more first data objects containing information relating to managing talents, a synchronization handler to obtain, based on identification features of the one or more first data objects, one or more second data objects from a storage device associated with the intelligent talent platform, calculate a consistency score based on values in the one or more first data objects and values in the one or more second data objects, and responsive to determining that the one or more first data objects comprise modifications from the one or more second data objects based on the consistency score, determine priority values associated with the modifications to the one or more first data objects.

Abstract: A method by one or more computing devices to standardize and centralize data movement between systems. The method includes receiving and storing data source information for a logical data source including authentication and authorization information for accessing a plurality of source systems that store data associated with the logical data source, schema information for a first schema used by a first one of the plurality of source systems to store data associated with the logical data source, and process information for a process including job information for a first job of the process that is for importing data associated with the logical data source from the first source system to a staging area. The method further includes executing the process according to the process information for the process.

Abstract: Systems and methods for managing file operations over shared content in the presence of two or more heterogeneous file systems. A virtual file system provides data consistency pertaining to asynchronous interactions between the heterogeneous storage systems. Operations of the virtual file system include receiving a file system call from a first storage environment for performing one or more data operations at a second storage environment. After receiving the file system call, the virtual file system issues file system calls to the second storage environment and records a first set of metadata. To determine if and when the one or more data operations at the second storage environment have completed, the virtual file system accesses a second set of metadata from the second storage environment. The two sets of metadata are compared. If there are differences, then the virtual file system performs time delays until the two sets of metadata agree.

Abstract: A system and method for propagating an opt-in through an identity graph fully honors opt-in requests without otherwise modifying the graph data structure. From a node corresponding to the touchpoint of the opt-in, the graph is traversed to find the associated primary node, from which all connected edges are traversed. Nodes on paths that are not connected to other primary nodes are opted in, along with the primary node. Edges that lead to nodes which have edges to other primary nodes are not opted in, but only the edge from the primary node itself is opted in. If household nodes are used, an identifier for the person at the household node may be opted in without opting in other members of the household node by opting in only the edge between the primary opt-in node and the household node.

Abstract: Techniques are disclosed relating to probabilistic data structures. A database node may maintaining a probabilistic data structure capable of encoding database keys. The probabilistic data structure may include a plurality of levels that are each capable of storing an indication of a transition between successive characters in a database key. The database node may insert a particular database key into the probabilistic data structure and the particular database key may comprise a series of characters. The inserting may include setting, for each transition between successive characters of the series of characters, an indication in a corresponding level of the plurality of levels that is indicative of that transition. The database node may further maintain lineage information specifying one or more lineages that correspond to the transition.

Abstract: A facility for distributing a search index for a corpus of documents is described. The facility accesses multiple search index segments collectively making up the search index. Each of the segments is executable to traverse an index subtree embedded in the segment to find in the index subtree a node representing a query term specified in an argument. Each of the segments corresponds to a particular indexed document field that is indexed by the search index. For each of the segments, the index subtree embedded the segment has nodes representing query terms that all produce a particular hash result. The facility calls a programmatic publication interface for a content delivery network to publish the plurality of search index segments on the content delivery network.

Abstract: Embodiments are directed to visualizing data using a graphical user interface (GUI) that may include a graph panel and a visualization panel arranged to receive inputs or interactions. A data model may be provided and displayed in the visualization panel. Input information that specifies portions of the data model may be provided to the visualization panel. Transform models may be determined based on the specified portions of the data model such that the determined transform models include a model interface that accepts the input information. The transform models may be employed to generate graph objects based on the data model, the input information such that the graph objects may be included in a graph model. Queries based on the graph model may be executed to provide results from the data model such that the results may be displayed in a visualization.

Abstract: Disclosed are embodiments for providing batch performance using a stream processor. In one embodiment, a method is disclosed comprising completing a first audit for a primary event type, the first audit generating a set of primary events and completing a second audit for a secondary event type, the second audit generating a draft set of secondary events and an auxiliary feed of un-joined secondary events. The method then performs a join audit check on the auxiliary feed of un-joined secondary events and a set of flags, each flag in the set of flags indicating that a respective un-joined secondary event was properly joined. Based on the results of the join audit check, the method replays a subset of the un-joined secondary events in the auxiliary feed upon determining that the join audit check failed.

Abstract: Embodiments of the present invention provide a computer system, a computer program product, and a method that comprises identifying a plurality of data logs; generating a data model using analyzed time series data from the identified data logs; detecting anomalies within the generated data model; constructing a causal graph using the detected anomalies and retrieved domain knowledge; computing a severity value for the detected anomalies with the constructed causal graph; assigning the detected anomaly to a classification based on a function vector, wherein the computed severity value is a function vector; and automatically modifying a function of a computing device based on the function vector of the assigned, detected anomaly, wherein a modification addresses the detected anomaly located at a center of the constructed casual graph.

Abstract: Data can be prefetched from a data storage system. For example, a computing device can receive a write request from a software application. The write request can be for writing a first data object to a storage device. The computing device can determine a second data object that is to be prefetched based on a read request for the first data object from the software application. The computing device can generate metadata for the first data object. The metadata can indicate that the second data object is to be prefeteched. The computing device can store the first data object with the metadata in the storage device.

Abstract: An illustrative embodiment disclosed herein is an apparatus including a processor having programmed instructions to update a versioned object by appending a latest version of the versioned object to a data structure, read a predetermined version identifier corresponding to the latest version from a pointer entry, and look up the latest version of the versioned object, in the data structure, using the predetermined version identifier corresponding to the latest version of the versioned object.

Abstract: A system for receiving and deduplicating data strings transmitted over a network is disclosed. The system comprises one or more network sensors detecting data strings while in transit on the network; and non-transitory memory comprising instructions. When the instructions are executed by one or more processors, the one or more processors establish a plurality of Bloom filters, receive a first data string, perform a first insertion operation into each Bloom filter; determine, for each of one or more Bloom filters, a set of bits, whether presently set or cleared, to be unset; and unset each determined set of bits in the one or more Bloom filters. At a later moment in time, the first data string is received again, and each Bloom filter is queried to determine whether the first data string has been inserted, based on a current state of that Bloom filter.

Abstract: Systems and techniques for aggregated physical and logical network mesh view are described herein. A selection may be obtained of a portion of a graph network data structure. Nodes may be identified in the portion of the graph network data structure. Geolocation data may be determined for each node of the nodes. Geographical boundaries may be calculated for the portion of the graph network data structure. A geographical map and a network map may be generated. A physical network view may be generated for display in the user interface as an aggregated view of the geographical map and the network map. The geographical map may represent a physical layer and the network map may represent a logical layer. The aggregated view may be output for display with a set of controls that correspond to the physical layer and a set of controls that correspond to the logical layer.

Abstract: Embodiments herein relate to replacing a legacy Pick environment with a modern microservice architecture. A legacy database and a modern database may be operated in parallel for data validation. During the validation process, the legacy database may be used as the master copy of the data. After verifying that the modern database satisfies the data needs of a system, the system can switch to using the new modern database as the master copy.

Abstract: A method of copying a production database to a test environment using one or more processors. The production database includes a plurality of tables and one or more constraints indicating interleaving of the plurality of tables. The method involves constructing a directed acyclic graph (DAG) of the plurality of tables, whereby each table is represented by a respective node of the DAG and interleaving of the tables is represented by edges of the DAG, topologically ordering the tables according to the DAG, and copying data from the production database to the test environment according to the topological ordering of the tables.

Abstract: Methods and systems are described herein for improving anomaly detection in timeseries datasets. Different machine learning models may be trained to process specific types of timeseries data efficiently and accurately. Thus, selecting a proper machine learning model for identifying anomalies in a specific set of timeseries data may greatly improve accuracy and efficiency of anomaly detection. Another way to improve anomaly detection is to process a multitude of timeseries datasets for a time period (e.g., 90 days) to detect anomalies from those timeseries datasets and then correlate those detected anomalies by generating an anomaly timeseries dataset and identifying anomalies within the anomaly timeseries dataset. Yet another way to improve anomaly detection is to divide a dataset into multiple datasets based on a type of anomaly detection requested.