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.

A processor may receive data and generate a quantified representation of the data by processing the data using at least one machine learning (ML) algorithm, the quantified representation of the data indicating a sentiment of content of the data. The processor may automatically revise the content of the communications data. The revising may include determining a reaction to the content of the communications data, generating a quantified representation of the reaction, determining a difference between the quantified representation of the reaction and the quantified representation of the communications data, identifying, based on the difference, a portion of the content having an unintended sentiment, and replacing the portion of the content with different content.

The present disclosure relates to systems and methods for matching electronic activities with record objects based on entity relationships. The method can include accessing a plurality of electronic activities, identifying an electronic activity, identifying a first participant associated with a first entity and a second participant associated with a second entity, determining whether a record object identifier is included in the electronic activity, identifying a first record object of the system of record that includes an instance of the record object identifier, and storing an association between the electronic activity and the first record object. The method can include determining a second record object corresponding to the second entity, identifying, using a matching policy, a third record object linked to the second record object and identifying a third entity, and storing, by the one or more processors, an association between the electronic activity and the third record object.

The present disclosure relates to systems and methods for matching electronic activities with record objects based on entity relationships. The method can include accessing a plurality of electronic activities, identifying an electronic activity, identifying a first participant associated with a first entity and a second participant associated with a second entity, determining whether a record object identifier is included in the electronic activity, identifying a first record object of the system of record that includes an instance of the record object identifier, and storing an association between the electronic activity and the first record object. The method can include determining a second record object corresponding to the second entity, identifying, using a matching policy, a third record object linked to the second record object and identifying a third entity, and storing, by the one or more processors, an association between the electronic activity and the third record object.

Methods and systems are presented for retrieving data associated with one or more portions of a graph by a computer system. Multiple graph indices are generated based on the graph. Each of the multiple graph indices stores records of data representing the graph in different formats. Upon receiving a request for accessing a sub-graph of the graph, edge-based attributes of the sub-graph are analyzed. The sub-graph may be divided into a first portion and a second portion of the sub-graph. A first graph index may be selected for retrieving records associated with the first portion of the sub-graph based on the edge-based attributes of the first portion of the sub-graph. A second graph index may be selected for retrieving records associated with the second portion of the sub-graph based on the edge-based attributes of the second portion of the sub-graph.

A system for data process comprises an operating platform for storing and reading a data unit. A data processing module signally connected to the operating platform. The data unit is structured or unstructured. The data processing module labeling and processing the data unit, and generating a visualization diagram. The system for data process includes a graphical user interface, which can achieve one of the purposes of this present disclosure of improving the data visualization of structured data and unstructured data.

Present invention discloses method and system for generating knowledge graph and sub-graph clusters to perform a root cause analysis. Method comprising extracting at least one of objects, data entities, links between the objects and the data entities, or relationships between the objects and the data entities from input content. Thereafter, method comprising generating a knowledge graph from the extracted data and sub-graphs from the knowledge graph using an unsupervised ML technique and extracting graph data structure information for each sub-graph. Subsequently, method comprising generating root cause model based on the sub-graphs and the graph data structure information and generating at least one sub-graph cluster and corresponding probabilistic graphical model using the root cause model and the knowledge graph. Generated Knowledge graph, root cause model and at least one sub-graph cluster and corresponding probabilistic graphical model are used to determine a root cause for an issue from an issue content.

A host, a storage system, and an operating method of the host are provided. The host includes a host memory configured to store a tree structure including a leaf node and an index node, an index management module configured to manage an index based on the tree structure and generate a first log corresponding to the leaf node based on a first update request corresponding to a first key-value entry included in the leaf node, and a device driver configured to generate a first write command corresponding to the first log and transmit the generated first write command to a key-value storage device, so as to store the first log in the key-value storage device. The index management module is configured to generate a first new key-value entry, the first new-key value entry including a first value updated based on the first update request, as the first log.

Methods and systems for presenting time series for analysis. A method may receive a first input defining a metric that indicates a relationship between a first and a second time series that are each associated with at least a first data object of a plurality of data objects, generate a first plot depicting the metric as determined from the first and the second time series, receive, via the user interface, a second input of a selection of a second data object of the plurality of data objects, determine, via an ontology, a relationship of the second data object with a third and a fourth time series that, respectively, are associated with series types that match series types associated with the first and the second time series, and generate and display, in the user interface, a second plot depicting the metric as determined from the third and the fourth time series.

A method may include presenting a user interface on a display device of a computing device, the user interface including: a search query input element; a plurality of graph type options; a graph level selection element; and a graph presentation area; receiving a search query inputted into the search query input element, the search query identifying a concept object in an ontology; retrieving data associated with the concept object from a graph database based on selections made in the graph type options and the graph level selection element, the data including a set of result objects related to the concept object; and rendering a hierarchical graph in the graph presentation area, the hierarchical graph illustrating the set of result objects and the concept object as interactive nodes.