Abstract: Example solutions are disclosed for performing a distributed data query for a connected data set, such as a property graph or a relational database, distributed across a plurality of regions (e.g., different geographic regions) under data flow limitations. For a restrictive limitation, a first region stores a data entity that is subject to a data flow limitation, and a second region stores only a reference to the data entity (e.g., a pseudonymous reference). The query is executed in the first region, and at least a partial representation of the state is injected into the query for execution in the second region. The query locates the reference to the data entity in the second region, and the state of the query from the second region is returned. Query results from the plurality of regions are synthesized into a final result. Further solutions address prohibitive limitations when references are not permitted.

Abstract: Methods and systems are disclosed for optimizing record placement in defragmenting a graph database. Issues with fragmented data within a graph database are addressed on the record level by placing data that is frequently accessed together contiguously within memory. For example, a dynamic rule set may be developed based on dynamically analyzing access patterns of the graph database, policies, system characteristics and/or other heuristics. Based on statistics regarding normal query patterns, the systems and methods may identify an optimal position for certain types of edges that are often traversed with respect to particular types of nodes.

Abstract: Examples of the present disclosure describe systems and methods for query execution across multiple graphs. In an example, a graph or isolated collection may be split into multiple subparts, such that each subpart may store information of the isolated collection. Cross-collection reference resources may be used to reference resources that are stored by other isolated collection subparts. A breadth-first search of an isolated collection subpart may be performed in order to identify matches or potential matches in an isolated collection subpart. In an example, a potential match may comprise a cross-collection reference resource, which may reference a resource in another isolated collection subpart. Once query execution has completed in the isolated collection subpart, query execution may be paused and transferred to another isolated collection subpart that comprises a resource referenced by a cross-collection resource reference.

Abstract: Example solutions balance traversals and precomputations for connected data sets subject to access control. When a request for a commutative operation on a connected data set is received, a downwardly recursive process starts with the current hierarchy tier set to a highest hierarchy tier of the request. The process traverses the current hierarchy tier laterally. At each discovered node in the current hierarchy tier, a determination is made whether the requested operation is permitted to include a discovered node. If not, that node and any nodes hierarchically below it are omitted from the operation. That node and its subtree are skipped and the recursion halts for that branch. If, however, the requested operation is permitted to include the node, it is incorporated into the cumulative result and the recursion continues while there remains a lower hierarchy tier. Some examples leverage precomputed aggregates to avoid traversing branches having aggregates.

Abstract: Examples of the present disclosure describe systems and methods for notifying users of content creation related to existing content expertise. In examples, content associated with a data domain is evaluated to determine the topics associated with the content. User activity for the data domain is monitored to determine user knowledge levels on various topics. User collaboration circles are determined based on interactions between users. When new content is detected, topics in the new content are evaluated and users having knowledge on the topics are identified based on the determined knowledge levels. The users having knowledge on the topics are ranked based in part on their collaboration circles. At least a portion of the ranked users having knowledge on the topics are notified of the new content creation and/or the users creating the new content are notified of the ranked users having knowledge on the topics.

Abstract: Example solutions are disclosed for performing a distributed data query for a connected data set, such as a property graph or a relational database, distributed across a plurality of regions (e.g., different geographic regions) under data flow limitations. For a restrictive limitation, a first region stores a data entity that is subject to a data flow limitation, and a second region stores only a reference to the data entity (e.g., a pseudonymous reference). The query is executed in the first region, and at least a partial representation of the state is injected into the query for execution in the second region. The query locates the reference to the data entity in the second region, and the state of the query from the second region is returned. Query results from the plurality of regions are synthesized into a final result. Further solutions address prohibitive limitations when references are not permitted.

Abstract: Examples of the present disclosure describe systems and methods for meeting analysis and coaching. In examples, a meeting is monitored to identify meeting content associated with the meeting. The meeting content is analyzed to determine participant content for the participants of the meeting. A knowledge level for topics discussed in the meeting is determined for each participant. A set of policies for the meeting is evaluated to determine whether the set of policies has been satisfied. A set of info including the participant content, the knowledge levels for the participants, the evaluation of the set of policies, and other information is evaluated to generate insights for the participants of the meeting. The insights are provided to the participants of the meeting.

Abstract: Described herein is a system and method for determining whether a detected issue in a computing system is a bug introduced by a developer or an intermittent issue. When an issue is detected, information about the issue is received. A determination is then made as to whether the issue is a new issue or whether it has been previously detected. When it is determined that the issue is a new issue, information about the issue is stored in a storage device. A feature vector is generated for the issue and is analyzed to determine a probability that the issue is a bug. When it is determined that the issue is a bug, the occurrence of the issue is reported to a user of the system that can correct the bug. Once the bug is corrected, the correction is provided back to the system and is used to train the system.

Abstract: Examples of the present disclosure describe systems and methods for preventing illicit data transfer and storage. In aspects, a computing platform may receive a data request from a caller system, device, or service. The computing platform may identify data items/properties associated with the data request and retrieve one or more rules relevant to the caller and/or caller location. The retrieved rule(s) may be used to evaluate the data item(s) such that data items, data item content, and/or data item properties that are prohibited by the retrieved rule(s) from being manipulated (e.g., accessed, transferred, stored) are removed from the identified data item(s). Based on the evaluation of the identified data item(s), one or more relevant status codes may be set. The computing platform may then manipulate the identified data item(s) in accordance with the data request and provide a processing response to the caller.

Abstract: Described herein is a system and method for determining whether a detected issue in a computing system is a bug introduced by a developer or an intermittent issue. When an issue is detected, information about the issue is received. A determination is then made as to whether the issue is a new issue or whether it has been previously detected. When it is determined that the issue is a new issue, information about the issue is stored in a storage device. A feature vector is generated for the issue and is analyzed to determine a probability that the issue is a bug. When it is determined that the issue is a bug, the occurrence of the issue is reported to a user of the system that can correct the bug. Once the bug is corrected, the correction is provided back to the system and is used to train the system.

Abstract: Examples described herein generally relate to a computer system for generating a knowledge graph storing a plurality of entities and to displaying a topic page for an entity in the knowledge graph. The computer system performs a mining of source documents within an enterprise intranet to determine a plurality of entity names. The computer system generates an entity record within the knowledge graph for a mined entity name based on an entity schema and the source documents. The entity record includes attributes aggregated from the source documents. The computer system receives a curation action on the entity record from a first user. The computer system updates the entity record based on the curation action. The computer system displays an entity page including at least a portion of the attributes to a second user based on permissions of the second user to view the source documents.

Abstract: Examples of the present disclosure describe systems and methods for determining authoritative documents based on implicit interlinking and communication signals. In aspects, a search operation may be initiated from one or more applications or services. The search operation may be processed to identify search information, such as one or more content items, content topics, or entities. The identified search information may be used to search one or more data sources for implicit relationships between the search information and content items and/or entities stored by the data sources. The results of the search may be collected and ranked according to one or more criteria. The ranked results may be provided in response to the search operation.

Abstract: Computerized systems are provided for detecting or receiving a sharing gesture in a communication group and responsively instantiating or updating one or more computer objects that include rich contextual data associated with the sharing gesture. These computer objects can be instantiated or updated based on one or more rules or policies. These computer objects or associated indications can be surfaced back to a user to give the user context regarding the shared resource. It can be determined whether a user has access to (or permission to access) such a computer object and/or an associated computer resource for presentation to the user.

Abstract: Examples of the present disclosure describe systems and methods for ontology-based graph query optimization. In an example, ontology data relating to a graph or isolated collection may be collected. The ontology data may comprise uniqueness and topology information and may be used to reformulate a query in order to yield a query that is more performant than the original query when retrieving target information from a graph. In an example, reformulating a query may comprise reordering one or more parameters of the query relating to resources, relationships, and/or properties based on uniqueness information. In another example, the query may be reformulated by modifying the resource type to which the query is anchored based on the topology information. The reformulated query may then be executed to identify target information in the isolated collection, thereby identifying the same target information as the original query, but in a manner that is more performant.

Abstract: Methods and systems are disclosed for optimizing record placement in a graph by minimizing fragmentation when writing data. Issues with fragmented data within a graph database are addressed on the record level by placing data that is frequently accessed together contiguously within memory. For example, a dynamic rule set may be developed based on dynamically analyzing access patterns of the graph database, policies, system characteristics and/or other heuristics. Based on statistics regarding normal query patterns, the systems and methods may identify an optimal position for certain types of edges that are often traversed with respect to particular types of nodes.

Abstract: Examples of the present disclosure describe systems and methods for ontology-based graph query optimization. In an example, ontology data relating to a graph or isolated collection may be collected. The ontology data may comprise uniqueness and topology information and may be used to reformulate a query in order to yield a query that is more performant than the original query when retrieving target information from a graph. In an example, reformulating a query may comprise reordering one or more parameters of the query relating to resources, relationships, and/or properties based on uniqueness information. In another example, the query may be reformulated by modifying the resource type to which the query is anchored based on the topology information. The reformulated query may then be executed to identify target information in the isolated collection, thereby identifying the same target information as the original query, but in a manner that is more performant.

Abstract: Methods and systems are disclosed for optimizing record placement in a graph by minimizing fragmentation when writing data. Issues with fragmented data within a graph database are addressed on the record level by placing data that is frequently accessed together contiguously within memory. For example, a dynamic rule set may be developed based on dynamically analyzing access patterns of the graph database, policies, system characteristics and/or other heuristics. Based on statistics regarding normal query patterns, the systems and methods may identify an optimal position for certain types of edges that are often traversed with respect to particular types of nodes.

Abstract: Examples of the present disclosure describe systems and methods for query execution across multiple graphs. In an example, a graph or isolated collection may be split into multiple subparts, such that each subpart may store information of the isolated collection. Cross-collection reference resources may be used to reference resources that are stored by other isolated collection subparts. A breadth-first search of an isolated collection subpart may be performed in order to identify matches or potential matches in an isolated collection subpart. In an example, a potential match may comprise a cross-collection reference resource, which may reference a resource in another isolated collection subpart. Once query execution has completed in the isolated collection subpart, query execution may be paused and transferred to another isolated collection subpart that comprises a resource referenced by a cross-collection resource reference.

Abstract: Examples of the present disclosure describe systems and methods for query execution across multiple graphs. In an example, a graph or isolated collection may be split into multiple subparts, such that each subpart may store information of the isolated collection. Cross-collection reference resources may be used to reference resources that are stored by other isolated collection subparts. A breadth-first search of an isolated collection subpart may be performed in order to identify matches or potential matches in an isolated collection subpart. In an example, a potential match may comprise a cross-collection reference resource, which may reference a resource in another isolated collection subpart. Once query execution has completed in the isolated collection subpart, query execution may be paused and transferred to another isolated collection subpart that comprises a resource referenced by a cross-collection resource reference.

Abstract: Methods and systems are disclosed for optimizing record placement in defragmenting a graph database. Issues with fragmented data within a graph database are addressed on the record level by placing data that is frequently accessed together contiguously within memory. For example, a dynamic rule set may be developed based on dynamically analyzing access patterns of the graph database, policies, system characteristics and/or other heuristics. Based on statistics regarding normal query patterns, the systems and methods may identify an optimal position for certain types of edges that are often traversed with respect to particular types of nodes.