Abstract: Methods comprising determining a dataset of entries, each comprising an entity identifier and associated application identifier(s) are provided. One method comprises determining a set of application pairs from the dataset; determining a correlation score for each application pair based; responsive to the correlation score exceeding a threshold correlation value: determining application identifiers of the application pair as being correlated; providing a correlation write request comprising the applications identifiers of the pair to an app recommender database.

Abstract: A content server can function as the master record keeper even if a file or folder that it manages in an enterprise computing environment is shared externally, for instance, through a cloud system. To mitigate network security risks, the content server polls, from behind a firewall, an event service of the cloud system. The event service, in response, can communicate events indicating changes to the shared content to the content server. The content server can interpret the events and determine whether to take any appropriate action, for example, updating an audit log to include an event and/or updating the managed content to reflect the changes. Likewise, the content server can communicate any change to the managed content to the cloud system through the event service. In this way, the managed content in the enterprise computing environment and the shared content in the cloud system are bidirectionally synced.

Abstract: Disclosed is an encoding system and associated methods for generating a graph-integrated tree-based representation of data that provides for direct lateral traversals of nodes in a each layer of the tree-based representation. The encoding system organizes data from a dataset to a tree-based representation with multiple layers and multiple nodes in each layer. The encoding system detects the nodes in each layer, and defines a graph structure that links the nodes in each layer for direct lateral access. The encoding system searches the tree-based representation in response to a query for a particular subset of the data by performing a single downward traversal to a particular layer with individual nodes that satisfy part of the query, and by laterally traversing the nodes in the particular layer using the graph structure to directly access a second node in the particular layer from a first node in the particular layer.

Abstract: A computing device includes processor(s), memory(s), and network interface(s). The processor(s) is configured to: cause the computing device to request mapping data for a particular physical location from a remote server using the at least one network interface; receive a unique identifier for the mapping data for the particular physical location from the remote server using the at least one network interface; cause the computing device to query a plurality of network nodes using the unique identifier to identify at least one network node of the plurality of network nodes that can provide the mapping data associated with the unique identifier, wherein the plurality of network nodes does not include the remote server; and receiving the mapping data from the at least one network node identified as being able to provide the mapping data associated with the unique identifier.

Abstract: In an embodiment, a first region is set according to a preset condition, the first region is a blank region reserved for storing new data of a key-value type. An embodiment method includes: when the new data of the key-value type is to be stored in the first region, receiving a region split command; updating, according to the region split command, a state identifier of the first region and in a state table to an identifier indicating that a read/write service is no longer provided, splitting the first region into at least two second regions, updating state identifiers of the second regions in the state table to identifiers indicating that a read/write service can be provided; and recording, in a metadata table, storage location information of the second regions.

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 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: 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 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: 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: During a checkout process in an online store, a user may provide data that facilitates future communication between the user and a merchant of the online store. However, this communication may be impeded when the user-provided data contains errors. Embodiments of the present disclosure provide systems and methods for resolving errors in user-provided data using stored datasets. According to one embodiment, a method includes determining that an identifier for an online order contains an error. The method also includes determining, based on a comparison between the identifier and multiple stored identifiers, that the identifier corresponds to a particular stored identifier within a defined tolerance. The method further includes generating an option for a user associated with the particular stored identifier to confirm an association between the particular stored identifier and the online order.

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: 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.

Abstract: Transactions include text fields, such as description fields. Transactions are extracted from financial institutions using web-scraping extraction. In the process of extracting transactions, errors can be introduced into text fields, such as the inclusion of a space within a word or the removal of a space between words. A statistical approach is applied to the text fields. When two alternative text fields are presented, the alternative that statistically includes more common tokens, such as unigrams and bigrams, is chosen as the correct alternative. The incorrect alternative is replaced by the correct alternative in the text field.

Abstract: A method for standardizing data input, data output and data manipulation at a data lake is provided. Methods include receiving a data transfer instruction comprising a seed file. Methods include parsing the seed file. Methods include validating the seed file. Methods include retrieving one or more data elements from one or more data sources as specified in the seed file. Methods include saving the retrieved data elements to a data lake. Methods include archiving the data elements at the data lake. Methods include receiving a schema from a network data mover client at an edge node at the data lake. Methods include creating a table to match the schema and validating the data elements using the schema. Methods include pushing the data elements into the table using the schema. Methods include saving the table that comprises the data elements in a shoreline edge node within the data lake.

Abstract: Various corpora of content objects and other information sources beyond the corpora of content objects are processed to identify personally identifiable information (PII). PII that is associated with a named person is codified into a first portion of a graph-oriented data structure. Also, PII that is associated with an alias that might refer to a named person is codified into a second portion of the graph-oriented data structure. A determination is made that the alias that might refer to a named person is indeed an alias that is a coreference to the named person. Based on that determination then, since the first portion of the graph and the second portion of the graph refer to the same person, then the PII of the second portion of the graph can be deemed to be PII of the same person. PII in common and/or language processing can be used to establish coreferences.

Abstract: Techniques are provided for finding unused vertex and edge identifiers (IDs) in a distributed graph engine. A run-time data structure may be built during the loading of the graph. The data structure identifies unavailable IDs that are associated with graph entities of the graph. The data structure is traversed to determine one or more ranges of free IDs. Unused IDs are generated from the ranges.

Abstract: Techniques are disclosed for storing an arranging data in a database. A method includes a computer system storing, in a database, data indicative of a graph data structure having a plurality of nodes connected by a plurality of edges. The method further includes the computer system determining that a number of edges connected to a first node satisfies a threshold number. In response to the determining, the computer system may store an index in an index row associated with the first node. The index identifies a first row having first and second ranges of values stored in first and second rows, respectively. The values in the first and second rows correspond to edges connected to the first node. The values in the first and second ranges are usable to indicate properties of corresponding ones of the plurality of edges.

Abstract: A plurality of different views of data associated with a storage domain stored on a deduplicated storage are traversed to determine data chunks belonging to each view of the plurality of different views of data associated with the storage domain. A request for a metric associated with disk space utilization of a group of one or more selected views of data included in the plurality of different views of data associated with the storage domain that are stored on the deduplicated storage is received. Data chunks belonging to the one or more selected views of data associated with the storage domain of the group but not other views of the plurality of different views of data associated with the storage domain that are stored on the deduplicated storage are identified. An incremental disk space utilization of the group is determined, including by determining a total size of the identified data chunks.

Abstract: Aspects of the present disclosure involve systems, methods, devices, and the like for generating highly scalable temporal graph databases. In one embodiment, a novel architecture is presented that enables the identification of mutation or changes in graphs. For the identification a combination of graph-based modeling and journal entry is used. Events occurring are consumed and changes are ingested, transformed for use by a graph simulation system. The changes are journaled using a vertex centric temporal journaling schema.