Abstract: A system for loading graph data from an external store in response to a graph query is disclosed. In some embodiment, given a graph database where all vertices are stored in memory and some but not all edges are stored in the external store, the system performs one of two methods. In the first method, the system iteratively expands a set of vertices that is initially specified in the graph query and collects all edges connected to the set of vertices, including edges stored in the external store, that satisfy a vertex constraint also specified in the query. In the second method, the system finds a set of vertices that satisfy the vertex constraint and collects all edges connected to the set of vertices, including edges stored in an external store.

Abstract: The present disclosure provides techniques for extracting structural information using machine learning. One example method includes receiving electronic data indicating one or more pages, constructing, for each page of the one or more pages, a tree based on the page, wherein each level of the tree includes one or more nodes corresponding to elements in a level of elements in the page, encoding, for each page of the one or more pages, a value of each node of the tree for the page into a vector using a first machine learning model, sampling a plurality of pairs of vectors from the one or more trees for the one or more pages, wherein a given pair of vectors corresponds to values of nodes in a same tree, training a second machine learning model using the plurality of pairs, and combining each vector with weights of the second machine learning model.

Abstract: A unified graph query system provides an abstraction layer that increases the interoperability of different graph technologies by exposing graphs stored in graph databases using a unified query language. The abstraction layer generates graph models for each of the available graph databases and extracts a graph component and other source data used to identify the source of the data requested by a query. The unified graph query system executes the query across the multiple graphs included in different graph databases by using the graph models to locate the graph component in each of the multiple graphs and extract the feature data associated with the graph component. The feature data is used to generate features that are used by a machine learning service to train machine learning models and is also used to make predictions in real time.

Abstract: Methods for cascade elimination of candidates in spatial relation operations are performed by systems, devices, and apparatuses. Spatial relation operations include counts of geometric objects against geographies/geometries, and data points associated with vertices of shapes representing the geographies/geometries are reduced to form smaller sets of data points that represent the initial shapes. Elimination of geometric objects for operations is performed using inner- and outer-reductions in cascade. Data points are reduced until a representation of the original shape with a specified area or number of data points is generated. Multi-polygon geometries are joined by union based on preservation of area and data points of the polygons therein prior to reducing data points. Cascade reductions are also performed at specified times during spatial operations based on costs associated therewith.

Abstract: Methods, systems, and computer program products for accelerating inference of transformer-based models are provided herein. A computer-implemented method includes obtaining a machine learning model comprising a plurality of transformer blocks, a task, and a natural language dataset; generating a compressed version of the machine learning model based on the task and the natural language dataset, wherein the generating comprises: obtaining at least one set of tokens, wherein each token in the set corresponds to one of the items in the natural language dataset, identifying and removing one or more redundant output activations of different ones of the plurality of transformer blocks for the at least one set of tokens, and adding one or more input activations corresponding to the one or more removed output activations into the machine learning model at subsequent ones of the plurality of the transformer blocks; and outputting the compressed version of the machine learning model to at least one user.

Abstract: Systems and methods to monitor veracity of a collection of one or more profiles associated with a user.

Abstract: A platform-agnostic input system can render a multiuser input board user interface element at one or more frontends to collect input from multiple users simultaneously. The platform-agnostic input system can maintain an object graph based on positions of objects added to the multiuser input board. The platform-agnostic input system can select branches of the object graph and determine which among a set of platforms in a multiplatform computing system to associate with the data associated with each node of that branch of the object graph.

Abstract: Various embodiments of the present disclosure relate to a computer-implemented method, a system, and a storage medium, where a graph stored in a computing system is logically divided into subgraphs, the subgraphs are stored on different interconnected (or coupled) devices in the computing system, and nodes of the subgraphs include hub nodes connected to adjacent subgraphs. Each device stores attributes and node structure information of the hub nodes of the subgraphs into other devices, and software or hardware prefetch engine on the device prefetches attributes and node structure information associated with a sampled node. A prefetcher on a device interfacing with the interconnected (or coupled) devices may further prefetch attributes and node structure information of nodes of the subgraphs on other devices. A traffic monitor is provided on an interface device to monitor traffic. When the traffic is small, the interface device prefetches node attributes and node structure information.

Abstract: The present disclosure includes an object to acquire information indicating a tendency on a visit spot for each vehicle sort. The present disclosure provides an information processing apparatus including a controller configured to execute: acquiring first information about a plurality of vehicles, the first information including vehicle information about a vehicle, the first information not being capable of identifying an individual user or an individual vehicle but reflecting at least part of attributes or preferences of a user associated with the vehicle, and spot information about a visit spot of the vehicle; and acquiring tendency information indicating a tendency on the visit spot of the vehicle for each vehicle classification based on the vehicle information, from the first information about the plurality of vehicles.

Abstract: Methods, computer readable media, and devices for securely managing interactions between distributed components are provided. One method may include generating a first interaction identifier based on a first component identifier and data to be shared with a second component, storing the first interaction identifier in an interaction data store of the first component, sending a request to the second component including the first component identifier, the first interaction identifier, and the data to be shared with the second component, creating a graph node in an interaction relationship data store based on the first interaction identifier, receiving a response from the second component including a second component identifier, a second interaction identifier, and response data, and adding a relationship edge in the interaction relationship data store connecting the graph node based on the first interaction identifier with a graph node based on the second interaction identifier.

Abstract: A method, apparatus, system, and computer program code for retrieving data records. A set of static configuration objects is provided, including: a set of resources that describe available data items, and a set of views that express a serialized transformation of resources objects into a response. In response to receiving a data request, a computer system generates a data fetch execution plan from the set of resources and the set of views. The data fetch execution plan is generated using an executor adapted to a particular data store and set of performance requirements. The computer system retrieves the data records according to the data fetch execution plan.

Abstract: A method for policy-based analytics includes retrieving, from a graph database, first data representing a first entity in a computing environment, a second entity in the computing environment, and an event associated with the first entity and the second entity; predicting, according to a risk indicator model, a risk associated with the first entity based at least in part on the event; and updating the graph database to include second data representing the risk and a risk indicator. The first and second entities are stored as properties of a first vertex and a second vertex, respectively, and the event is stored as a property of an edge between the first vertex and the second vertex. The risk indicator is stored as a property of a third vertex. The risk is stored as a property of an edge between the first vertex and the third vertex.

Abstract: Provided are systems and methods for personalizing website content configured for delivery to a user. An exemplary system includes a graph database for storage of data (i) representative of the user's interaction with existing content presented on the website and (ii) indicative of content entities of interest to the user, the data being stored as nodes. Also included are one or more personalization engines configured to analyze relations between one or more pairs of the nodes, each analyzed relation creating a respective link, and a structure of each of the links being a function of the user's interaction with the existing content. The one or more processors are configured to personalize new content for presentation to the user and a portion of the new content is (i) derived from one of the respective links and (ii) delivered to the user in near-real time when a type of the first link is within a first category.

Abstract: Managing connected data, such as a graph data store, includes a computing device with persistent memory and volatile memory. The computing device stores a graph data store with a plurality of nodes and edges in persistent memory. Each of the edges defines the relationship between at least two of the nodes. The nodes and edges may contain tags and properties containing additional information. In response to a search request query, the computing device generates an iterator object stored in volatile memory with a reference to one or more nodes and/or edges in the graph data store. The split between volatile and persistent memory allocation could be used for other objects, such as allocators and transactions. Other embodiments are described and claimed.

Abstract: Machine learning based techniques are described for identifying sanctionable persons via monitoring a plurality of electronic content sources. This may allow for more rapid identification of prohibited or restricted transactions. A trained sentiment analysis classifier may classify a particular electronic content item as containing sanctionable conduct. An electronic textual analysis of the electronic content item may be performed to identify one or more individual names within the particular electronic content item. An indication as to whether the one or more individual names have been identified as individuals who may be subject to one or more sanction requirements that prohibit one or more online actions may be electronically stored in a data table. Various operations may be performed to block or otherwise restrict online accounts associated with the individual from performing online activities.

Abstract: Techniques are described for reducing the number of parameters of a deep neural network model. According to one or more embodiments, a device can comprise a memory that stores computer executable components and a processor that executes the computer executable components stored in the memory. The computer executable components can comprise a structure extraction component that determines a number of input nodes associated with a fully connected layer of a deep neural network model. The computer executable components can further comprise a transformation component that replaces the fully connected layer with a number of sparsely connected sublayers, wherein the sparsely connected sublayers have fewer connections than the fully connecter layer, and wherein the number of sparsely connected sublayers is determined based on a defined decrease to the number of input nodes.

Abstract: A process including obtaining a set of natural-language text documents that discuss a topic, the set of documents containing different states of knowledge about the topic at different times. The process includes selecting an ontology from among a plurality of ontologies that correspond to different domains of knowledge, the selection being based on the ontology corresponding to a domain of knowledge including the topic. The process includes identifying concepts discussed in the documents using the ontology and detecting changes in at least some of the concepts over time based on differences between discussion of the concepts in documents authored at different times. The process includes updating natural language instructions on the topic based on the detected changes in the concepts and storing the updated natural language instructions in memory.

Abstract: An online concierge system generates an item graph connecting item nodes with attribute nodes of the items. Example attributes include a brand, a category, a department, or any other suitable information about the item. When the online concierge system receives a search query to identify one or more items from a customer, the online concierge system parses the search query into combinations of terms and identifies item nodes and attribute nodes related to the search query. The online concierge system identifies item nodes and attribute nodes that are likely to result in a conversion. Information about the identified nodes is presented to the customer. The customer may select an item node to purchase the item, or an attribute node to execute a new search query based on terms associated with the attribute node.

Abstract: An apparatus links an entity in a first knowledge-graph with a word in a text. The apparatus, based on a number of first-edges coupled to each of first-nodes serving as a transition-source and a number of second-edges coupled to each of second-nodes serving as a transition-destination in the first knowledge-graph, identifies a third-edge to be deleted from edges coupled to a third-node among the second-nodes which has a preset input-order indicating a number of edges that transition to the third-node, and generates a second knowledge-graph by deleting the third-edge from the first knowledge-graph. The apparatus couples first and second nodes which have been coupled to each other by the third-edge in the first knowledge-graph, via a fourth-node to which the first and second nodes are coupled by edges in the second knowledge-graph, and provides the word in the text and the entity linked with the word to a user.

Abstract: The present disclosure describes techniques for using instances of a connector to communicate with multiple target systems without a manual pre-configuration step for each of the multiple target systems. The connector may be an extensible program-code-template for creating objects to perform one or more operations. For example, each instance of the connector may obtain information regarding a corresponding target system, determine an interface to the corresponding target system based on the information, and translate requests for the corresponding target system according to the interface.

Abstract: Techniques herein minimally communicate between computers to repartition a graph. In embodiments, each computer receives a partition of edges and vertices of the graph. For each of its edges or vertices, each computer stores an intermediate representation into an edge table (ET) or vertex table. Different edges of a vertex may be loaded by different computers, which may cause a conflict. Each computer announces that a vertex resides on the computer to a respective tracking computer. Each tracking computer makes assignments of vertices to computers and publicizes those assignments. Each computer that loaded conflicted vertices transfers those vertices to computers of the respective assignments. Each computer stores a materialized representation of a partition based on: the ET and vertex table of the computer, and the vertices and edges that were transferred to the computer. Edges stored in the materialized representation are stored differently than edges stored in the ET.

Abstract: A computer-implemented method of retrieving and displaying data from an entity network database (130) comprising a plurality of entities and a plurality of relationships between the entities is provided. The method comprises receiving a selection of a plurality of anchor entities of the entity network database; retrieving a plurality of connector entities of the entity network database, each connector entity disposed on a path in the entity network database extending between at least two of the anchor entities; determining a relevance score for each of the connector entities, the relevance score reflecting the relevance of each connector entity to the anchor entities; and displaying the connector entities within a shape defined by the anchor entities, wherein the distance of each connector entity from the anchor entities is based on the relevance score of the connector entity.

Abstract: Methods, non-transitory machine readable media, and computing devices that provide more efficient hierarchical propagation in tree structures are disclosed. With this technology, a first delta record for a first interior node is created optionally in an atomic transaction along with updating a first tally record for a leaf node based on a first value. The transaction is in response to an action associated with the leaf node and the first interior node is a parent of the leaf node in a hierarchical tree. A timer associated with the first delta record is then set. A second value is updated in a second tally record for the first interior node based on the first value, when the timer has expired. Accordingly, this technology advantageously maintains recursive properties or values throughout a hierarchical tree continually, with reduced cost, even in a distributed network and in hierarchical trees with large numbers of nodes.

Abstract: In one embodiment, a method includes, by a client system of a user of an online social network, sending, to one or more computing devices of the online social network, a text post inputted by the user. The text post is associated with a query. The method includes receiving, from the one or more computing devices in response to the text post, an initial recommendation list. The initial recommendation list includes references to one or more objects referenced in comments associated with one or more prior posts associated with the query. The method includes sending, to the one or more computing devices, a request for updates to the initial recommendation list. Moreover, the method includes receiving, from the one or more computing devices in response to the request, an updated recommendation list comprising references to one or more objects referenced in comments associated with the text post.

Abstract: In general, embodiments of the invention relate to a method and computing system for scheduling tasks (functions or routines) dynamically from Input/Output (I/O) operations that may be received from a client. The scheduling or ordering of the tasks play an important role in the overall latency of the execution of IO operations, as each task may consume significant amount of computing resources.

Abstract: Systems and techniques are provided for mutable data ingestion and storage. Data for a database may be received at a computing device. New data from the data for the database may be stored as a mutable data chunk. The data for the database may be determined to include updated data for a previously stored mutable data chunk. The updated data may be applied to the previously stored mutable data chunk to update the previously stored mutable chunk. A second previously stored mutable data chunk may be determined to have been initially stored a specified amount of time ago. In response to determining that the second previously stored mutable data chunk was initially stored the specified amount of time ago, the second previously stored mutable data chunk may be caused to become an immutable data chunk.

Abstract: One embodiment provides a method and system for joint payment. During operation, a joint-payment server receives a joint-payment request comprising an identifier of a user initiating a joint payment and an identifier of a user to-be-included in the joint payment; determines, based the identifiers of the user initiating the joint payment and the to-be-included user, whether a binding relationship has been established between the user initiating the joint payment and the to-be-included user; in response to determining that the binding relationship has been established, generates graphic codes respectively corresponding to the user initiating the joint payment and the to-be-included user; and sends the graphic codes to a terminal device associated with the user initiating the joint payment, thereby facilitating the terminal device to display the graphic codes to complete the joint payment.

Abstract: Embodiments of the present invention determines duplicates in a graph. The graph comprises nodes representing entities and edges representing relationships between the entities. The method comprises: identifying at least two nodes in the graph. A neighborhood subgraph may be determined for each of the two nodes. The neighborhood subgraph includes the respective node. The method further comprises determining whether the two nodes are duplicates with respect to each other, based on a result of a comparison between the two subgraphs.

Abstract: An information management apparatus includes a processor configured to associate components including questions and answers to the questions using parent-child relationships and control a display of the components as a tree structure, receive a selection of a subset of components in the tree structure according to a user operation and also connect the selected subset of components to the tree structure, and change the parent-child relationships of the components according to the connection of the components.

Abstract: Methods and systems are provided for determining the category of a software application utilizing machine learning (ML) and knowledge graph techniques, and for controlling access to the application by a user based on the category and configured time restrictions for the user. The system includes a feature set extractor and a category predictor with a trained ML model. The trained ML model generates the category of the application based on a feature(s) of the application. The generated category is indicated in a data structure. An access request handler receives a request related to access to the application from a user device. A category determiner determines the category of the application from the data structure. A time usage manager determines an available time usage for the category and the specified user. The access arbiter responds to the request from the user device with the available time usage.

Abstract: Systems and methods for updating values of roll-up summary fields (RSFs) associated with a data model are described. A server computing system receives data associated with roll-up summary fields (RSF) of objects of a data model. The data is in in a serialized format. The computer system deserializes the data to determine values of the RSFs at nodes of a graph associated with the data model. The computer system updates a value of a RSF at a first node of the graph. The computer system updates a value of one or more RSFs at one or more remaining nodes of the graph based on said updating the value of the RSF at the first node. The computer system serializes the values of the RSFs at all of the nodes of the graph to generate serialized data subsequent to said updating the value of the one or more RSFs at the one or more remaining nodes of the graph.

Abstract: A method, apparatus and server for recommending an application are provided. The method may include determining at least one target friend among a plurality of friends of a target user, obtaining social interaction characteristics between the target user and the at least one target friend, based on a pre-trained friend impact prediction model of a target application and the social interaction characteristics between the target user and the at least one target friend, determining a first impact of the at least one target friend on registration of the target user in the target application, determining a recommendation score corresponding to the target user and the target application according to the first impact of the at least one target friend on registration of the target user in the target application, and performing application recommendation according to the recommendation score.

Abstract: A graph updating device includes: a K neighbor vertex search unit that searches for a K neighbor vertex set of an added vertex in a neighbor graph on the basis of the neighbor graph and an object added to the neighbor graph as an added vertex and outputs the K neighbor vertex set; a vertex selection unit that selects a vertex candidate set on the basis of the neighbor graph, the added vertex, and the K neighbor vertex set of the added vertex and outputs the vertex candidate set, the vertex candidate set being a set of vertices that is present in the neighbor graph and possibly contains the added vertex in a K neighbor vertex set thereof; and a neighbor graph updating unit that reconstructs a K neighbor vertex set related to all vertices of the neighbor graph using K neighbor vertex sets of respective vertices of the vertex candidate set and adds the K neighbor vertex set of the added vertex to the reconstructed K neighbor vertex set to generate an updated neighbor graph.

Abstract: A method for increasing a speed or energy efficiency at which a computer is capable of modeling a plurality of random walkers. The method includes defining a virtual space in which a plurality of virtual random walkers will move among different locations in the virtual space, wherein the virtual space comprises a plurality of vertices and wherein the different locations are ones of the plurality of vertices. A corresponding set of neurons in a spiking neural network is assigned to a corresponding vertex such that there is a correspondence between sets of neurons and the plurality of vertices, wherein a spiking neural network comprising a plurality of sets of spiking neurons is established. A virtual random walk of the plurality of virtual random walkers is executed using the spiking neural network, wherein executing includes tracking how many virtual random walkers are at each vertex at a given time increment.

Abstract: A method of updating a server knowledge graph, is performed by a server and includes obtaining a server knowledge graph of the server, and obtaining a plurality of device knowledge graphs by receiving a device knowledge graph from each of a plurality of devices. The method further includes generating a knowledge graph for server knowledge graph extension, based on the obtained plurality of device knowledge graphs, and updating the obtained server knowledge graph, using the generated knowledge graph for server knowledge graph extension.

Abstract: Systems and methods are described for utilizing non-serializable object parameters with a function as a service (“FaaS”) platform. A user can select, in a user interface of a web application, a server and a command for executing in a shell client. The web application can generate instructions for constructing an object in a shell client that corresponds to the server. The web application can retrieve a shell script associated with the selected command. The web application can send the instructions and shell script to a FaaS. The FaaS can execute, in a shell client, a script that constructs the object as a parameter in a shell session. In the same shell session, the FaaS can execute the shell script, causing the shell client to use the object as a parameter for the shell script.

Abstract: A method of updating a server knowledge graph, is performed by a server and includes obtaining a server knowledge graph of the server, and obtaining a plurality of device knowledge graphs by receiving a device knowledge graph from each of a plurality of devices. The method further includes generating a knowledge graph for server knowledge graph extension, based on the obtained plurality of device knowledge graphs, and updating the obtained server knowledge graph, using the generated knowledge graph for server knowledge graph extension.

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: An aspect of space accounting includes providing a counter for each of a plurality of key/value pairs for storage system operations. The key uniquely identifies a logical storage unit on which operations associated with the key are performed, the value identifies an amount of data usage with respect to the operations performed on the logical storage unit, and the counter tracks a type of the operations. An aspect also includes tracking, via corresponding counters, updates to a read/write (RW) tablet associated with a Cuckoo tree. The tracking includes updating a filter to include instances of key/value pairs and the RW tablet in which the pairs are stored. An aspect further includes tracking a plurality of read-only (RO) tablets associated with the Cuckoo tree. The tracking includes updating the filter to include instances of key/value pairs and one or more of the RO tablets in which the pairs are stored.

Abstract: A hyper-graph sketching framework receives graph data set to generate non-singular reverse cascades in a network to assess influence dynamics therein. A high-quality influence oracle for seed sets uses the resulting sketch data set generated from the non-singular reverse cascades to output estimation of influence.

Abstract: A method and system are provided for multifactor identification of a subject over a network using a rich credential, with selective disclosure of attributes and selective presentation of verification factors. A credential presentation application negotiates with a verifying server to agree on attributes to be disclosed and verification factors to be presented, and removes unneeded attributes and verification data from the rich credential by pruning subtrees from a typed hash tree without invalidating a signature that covers the root label of the tree. The credential presentation application proves knowledge of a private key, and as agreed upon may prove knowledge of a password and may arrange for biometric presentation applications to present one or more biometric samples to the verifier, which performs presentation attack detection and verifies the samples against verification data in the rich credential.

Abstract: Techniques are provided for predicting and deleting idle remote sessions in a distributed file system. In an example, a server that serves a plurality of server message block (SMB) sessions analyzes with linear regression techniques those sessions to determine which sessions will become idle. In some examples, the server can then proactively close a SMB session that it predicts that an administrator would choose to close after a given idle period of time, or recommend to an administrator that the SMB session can be closed.

Abstract: An approximate count of a subset of records of a data set is obtained using one or more transformation functions. The subset comprises records which contain a first value of one input variable, a second value of another input variable, and a particular value of a target variable. Using the approximate count, an approximate correlation metric for a multidimensional feature and the target variable is obtained. Based on the correlation metric, the multidimensional feature is included in a candidate feature set to be used to train a machine learning model.

Abstract: A document-oriented database system generates an optimal query execution plan for database queries on an untyped data field included in a collection of documents. The system generates histograms for multiple types of data stored by the untyped data field and uses the histograms to assign costs to operators usable to execute the database query. The system generates the optimal query execution plan by selecting operators based on the assigned costs. In various embodiments, the untyped data field stores scalars, arrays, and objects.

Abstract: A system and method for dynamically determining a trust level of an end-to-end link of a computer database, including: in a preparation stage: capturing a first set of messages of an end-to-end link; compressing a skeleton of each message of the first set of messages to generate a construct of each message of the first set of messages, the skeleton includes the message without a value field; creating a characteristic histogram of the constructs of the first set of messages; and during an operation stage: capturing a second set of messages of the end-to-end link; compressing a skeleton of each message of the second set of messages to generate a construct of each of the second set of messages; creating a work histogram of the constructs of the second set of messages; and determining a trust level of the end-to-end link by comparing the work histogram with the characteristic histogram.

Abstract: According to an implementation, a method for digital information retrieval in a social media platform includes transmitting, over a network, information to render a timeline of social content for a user of a client application. The timeline of social content includes messages posted on the messaging platform by user accounts that are connected to a user account of the user in a connection graph. The method includes computing, using a machine-learning algorithm inputted with relevance signals, a relevance level between the user account of the user and a user account not linked to the user account of the user in the connection graph, and transmitting information about a profile of the user to a computing device associated with the user account not linked to the user account of the user in response to the relevance level being greater than a threshold level.

Abstract: A method, computer program product, and a system where a processor(s) obtains, from a data source, a list of objects at different layers of a computing system. The processor(s) generates exploration lists from the list (each exploration list with objects for a layer). The processor(s) identifies updated and new data at the layers associated with the objects on the list; the identified data comprises attributes for each layer. The processor(s) applies machine learning algorithm(s) to enrich the data by identifying dependencies between the attributes for each layer as influencers for one or more key performance indicators of the computing system. The processor(s) generates, from the enriched data, a hierarchy matrix. The processor(s) determines, based on the hierarchy matrix that an event associated with one or more computing resources of the computing system will influence a particular key performance indicator.

Abstract: Methods and apparatus that allow clients to specify custom network rules for their resource instances or network constructs in a provider network environment. Services and interfaces may be provided that allow a client to provide an executable module that implements custom rules for their resources, or alternatively to specify or select custom rules for their resources. The module may be installed on a host device, and may apply the custom rules to packets to and from the client's resources. Alternatively, the client-defined rules may be applied to packet flows according to the custom rules specified by the client and applied by a client rules service implemented on the provider network external to the host device or on a client resource instance on the host device. The custom network rules may, for example, extend or modify standard network rules for the client's resources on the host device.

Abstract: Techniques are described herein for early pruning of potential graph query results. Specifically, based on determining that property values of a path through graph data cannot affect results of a query, the path is pruned from a set of potential query solutions prior to fully exploring the path. Early solution pruning is performed on prunable queries that project prunable functions including MIN, MAX, SUM, and DISTINCT, the results of which are not tied to a number of paths explored for query execution. A database system implements early solution pruning for a prunable query based on intermediate results maintained for the query during query execution. Specifically, when a system determines that property values of a given potential solution path cannot affect the query results reflected in intermediate results maintained for the query, the path is discarded from the set of possible query solutions without further exploration of the path.

Abstract: A dataset management system organizes datasets using a data relationship graph that serves as a representation of datasets that are related to one another. For example, the data relationship graph includes nodes that each represent a dataset as well as edges that each connect two nodes. Each edge represents a similarity in characteristics of the similar datasets such as a similarity in the datasets' origin, organizational schema, lineage, or data values. When a user is to be provided recommended datasets, the dataset management system identifies candidate datasets by traversing the nodes and edges of the data relationship graph. Amongst these candidate datasets, the dataset management system evaluates users that have accessed the candidate datasets as well as the context in which the candidate datasets were accessed to identify recommended datasets for presentation to the user.