Abstract: Techniques are disclosed for tuning external invocations utilizing weight-based parameter resampling. In one example, a computer system determines a plurality of samples, each sample being associated with a parameter value of a plurality of potential parameter values of a particular parameter. The computer system assigns weights to each of the parameter values, and then selects a first sample for processing via a first external invocation based on a weight of the parameter value of the first sample. The computer system then determines feedback data associated with a level of performance of the first external invocation. The computer system adjusts the weights of the parameter values of the particular parameter based on the feedback data. The computer system then selects a second sample of the plurality of samples to be processed via execution of a second external invocation based on the adjustment of weights of the parameter values.

Abstract: Techniques are disclosed for deploying a computing resource (e.g., a service) in response to user input. A computer-implemented method can include operations of receiving (e.g., by a gateway computer of a cloud-computing environment) a request comprising an identifier for a computing component of the cloud-computing environment. The computing device receiving the request may determine whether the identifier exists in a routing table that is accessible to the computing device. If so, the request may be forwarded to the computing component. If not, the device may transmit an error code (e.g., to the user device that initiated the request) indicating the computing component is unavailable and a bootstrap request to a deployment orchestrator that is configured to deploy the requested computing component. Once deployed, the computing component may be added to a routing table such that subsequent requests can be properly routed to and processed by the computing component.

Abstract: Data can be received that includes information corresponding to a set of users. Privacy protection protocols that apply to the data can be identified. A subset of the data can be identified as being personally identifiable information (PII) data, where the subset includes a set of PII attributes. The PII attributes can be split into categories based on a format of a data field in the PII attributes. The processed PII data can be combined with non-PII data to create processed client data. It can be determined to add noise to part of the processed PII data. An amount of noise can be determined based on the privacy protection protocols. The amount of noise can be added to part of the processed PII data to produce protected data. A machine-learning model can be trained using the protected data.

Abstract: Novel techniques are disclosed that enable the creation of a two-tier marketplace comprising a CSP marketplace and one or more marketplaces for virtual private label clouds (vPLCs). Each marketplace can be created and operated independently. In some embodiments, a publisher may publish a solution offering directly on a vPLC marketplace without involving the CSP marketplace. In other embodiments, a solution offering published on a marketplace may be automatically republished on another marketplace. Yet, in another embodiment, a customer subscribing to a vPLC marketplace can see a composite view of a directly published solution listing and a republished solution listing.

Abstract: Aspects of the present disclosure include implementing fabric availability and synchronization (FAS) agents within a fabric network. In one example, a first FAS agent executing on a first network device may receive, from a second network device, a command to modify a configuration of a second network device. The first FAS may upgrade the configuration of the first network device based on the command from a current configuration to a new configuration. The first FAS agent increment a state identifier associated with the configuration of the first network device to a new state identifier associated with the new configuration. The first FAS agent may then transmit a control packet that includes the new state identifier. A second FAS agent executing on the second network device may receive the control packet and execute the command to update the configuration of the second network device to the new configuration.

Abstract: Novel techniques are disclosed for enabling customizable consoles of different virtual private label clouds (vPLCs). In some embodiments, one console server may execute multiple consoles for multiple vPLCs and CSP. In other embodiments, one console server may be dedicated to a vPLC-specific console. In certain embodiments, console customization including a customized set of console user interfaces (UIs) may be performed for each vPLC-specific console.

Abstract: A secure private network connectivity system (SNCS) within a cloud service provider infrastructure (CSPI) is described that provides secure private network connectivity between external resources residing in a customer's on-premise environment and the customer's resources residing in the cloud. The SNCS provides secure private bi-directional network connectivity between external resources residing in a customer's external site representation and resources and services residing in the customer's VCN in the cloud without a user (e.g., an administrator) of the enterprise having to explicitly configure the external resources, advertise routes or set up site-to-site network connectivity.

Abstract: Techniques for predicting marketing outcomes using contrastive learning are disclosed, including: obtaining historical marketing messages; obtaining historical open rates associated respectively with the historical marketing messages; based on the historical marketing messages, generating latent space representations associated respectively with the historical marketing messages; based on the latent space representations and respective contents of the historical marketing messages, training a first machine learning model to map contents of marketing messages to corresponding latent space representations of the marketing messages; based at least on the latent space representations and the historical open rates, training a second machine learning model to map latent space representations of marketing messages to predicted open rates of the marketing messages.

Abstract: Novel techniques are disclosed for providing vPLC-specific metadata service including customized vPLC-specific metadata. In certain embodiments, each vPLC may generate a customized metadata using its corresponding vPLC-specific customization instructions. In some embodiments, a vPLC-specific metadata service may be performed using pre-generated customized vPLC-specific metadata, on-the-fly customized metadata, pre-generated CSP-format metadata, or combinations thereof.

Abstract: Techniques are described herein for applying access controls to logical secure elements (LSEs) running on the same secure element hardware platform. Embodiments include a firmware component that determines whether a message targeting an LSE is authorized to trigger an operation. For example, the firmware component may verify a signature of the received message using a public key, shared secret, or other access control key. Additionally or alternatively, access control policies may be defined to constrain the load of the LSEs on the SE platform hardware and/or to prioritize LSE access. For example, the access control policies may define usage thresholds, such as maximum threshold memory and/or processor utilization rates. As another example, the access controls may restrict the active time for an LSE to a threshold duration. If access constraints are violated or the message cannot be verified, then the firmware component may delay or deny the operation.

Abstract: Systems and methods for route mismatch identification are disclosed herein. A method of route mismatch identification can create in cache an expected routing table based on expected routing information received by a routing agent of a host from a database accessible by each of the plurality of hosts. The method can include creating in cache an actual routing table based on actual routing information received by the routing agent of the host from an advertising agent of the host, comparing the actual routing table and the expected routing table, and taking an action based on the comparison of the actual routing table and the expected routing table.

Abstract: The disclosed systems, methods and computer readable media relate to managing Non-Volatile Memory Express (NVMe) over Transmission Control Protocol (TCP) (NVMeOTCP) connections between a smart network interface card (smartNIC) and a block storage data plane (BSDP) of a cloud computing environment. A software agent (“agent”) executing at the smartNIC may manage a number of network paths (active and, in some cases, passive network paths). The agent may monitor the network traffic (e.g., input/output operations (IOPS)) through the paths (e.g., using established NVMeOTCP connections corresponding to the paths). If a condition is met relating to a performance threshold associated with the monitored paths, the agent may increase or decrease the number established NVMeOTCP connections to match real time network conditions.

Abstract: Techniques for facilitating connectivity to vPLCs created in a CSP-provided infrastructure in a region. Within the CSP-provided infrastructure in a region, when the destination of a packet is determined to be an endpoint associated with a particular vPLC, the packet is tagged with information related to the particular vPLC. The vPLC-related information for the particular vPLC can include, for example, a vPLC identifier identifying the particular vPLC, an identifier identifying a customer associated with the endpoint, a virtual cloud network identifier identifying a virtual cloud network (VCN) belonging to the particular vPLC and where the endpoint is part of the VCN, and other vPLC-related information. The packet is then routed or communicated within the CSP-provided infrastructure in a region along with the tagged vPLC-related information. The vPLC-related information is used as part of the connectivity and for routing of packets within the CSP-provided infrastructure in a region.

Abstract: Novel techniques for resource usage monitoring, billing, and enforcement for virtual private label clouds (vPLCs) are disclosed. In some embodiments, resource usage for a vPLC associated with a reseller is monitored at both reseller level and customer-of-reseller level using resource IDs, and stored as usage information in two levels and associated with a tenancy ID for the reseller (at the reseller level) and tenancy IDs for customers of the reseller (at the customer-of-reseller level). In some embodiments, a two-level billing process generates invoices using two-level pricing information and the generated invoices to either resellers or customers of resellers directly. In some embodiments, usage enforcement can be performed per vPLC or per customer tenancy of a reseller's customer.

Abstract: Techniques for generating supplemental information based on runbook operation results are disclosed. A system generates and displays supplemental information for a runbook execution interface based on one of a system component associated with an executable operation of a runbook, and a set of runbook operation results corresponding to the executable operation. The system receives a user input to execute an operation defined by a runbook presented to remediate an event. The system generates supplemental information for the runbook execution interface based on the results of the operation executed by the user. The system identifies characteristics associated with the runbook operation results and identifies sources for additional information. Source may include performance data from the same component over a different period of time, performance data of a similar component, and performance data of topologically-connected components.

Abstract: Techniques discussed herein relate to providing in-memory workflow management at an edge device (e.g., a computing device distinct from and operating remotely with respect to a data center). The edge device can operate as a computing node in a computing cluster of edge devices and implement a hosting environment (e.g., a distributed data plane). A work request can be obtained by an in-memory workflow manager of the edge device. The work request may include an intended state of a data plane resource (e.g., a computing cluster, a virtual machine, etc.). The in-memory workflow manager can determine the work request has not commenced and initialize an in-memory execution thread to execute orchestration tasks to configure a data plane of the computing cluster according to the intended state. Current state data corresponding to the configured data plane may be provided to the user device and eventually displayed.

Abstract: A blockchain architecture allows blocks to store both public and private data. The public data may be accessible to any node in the blockchain network, while the private data may be accessible only to nodes specified in an access list, which may be provided when a record is added to the blockchain. When a new record is received, any private fields in the record may be identified and encrypted by a receiving node. The key may then be encrypted and sent with the protected record to other nodes in the access list. These nodes can access the encryption key, decrypt the private fields, and provide a consensus decision to a receiving node. After consensus, the protected record may be added to the blockchain, where the public fields may be freely accessed by any node, and the private fields remain accessible only to nodes in the access list.

Abstract: A method, a non-transitory computer readable medium, and an apparatus are provided for switching between a synchronous data entry processing and an asynchronous data entry processing for processing input into a data entry field of the GUI based on a latency threshold for validation and a latency threshold for conversion; and for determining which input from a series of inputs entered into the data field during the asynchronous data entry processing based on a criteria.

Abstract: Embodiments include systems and methods for managing a network of nodes with delta processing. A network with a plurality of connected nodes can be stored, the nodes representing entities of the network. One or more deltas to the network that indicate updates to the connections among the plurality of nodes can be received. The deltas can be added to a queue. The connections between the nodes of the network can be updated using a delta from the queue. The network can be processed after updating the connections between the nodes to generate a vector for a given node. One or more paths for the given node can be identified based on the generated vector.

Abstract: Techniques are described for improving the efficiency of dialog processing by prompting and processing user feedback substantially in real time. A dialog system receives speech input from a user and processes a first portion of the speech input to determine an initial discerned intent. The dialog system causes display of a visual indication of the initial discerned intent. The visual indication of the discerned intent is used to guide the dialog so that the user can correct or confirm the initial discerned intent in a natural fashion. If the initial discerned intent is inaccurate, the user can provide feedback correcting the dialog system, and the dialog system processes a second portion of the speech input to determine a modified discerned intent. Thus, the dialog system can use the feedback to correct misunderstandings on the fly.

Abstract: Techniques for determining a data tape read quality value are disclosed. A data tape system generates a value representing a quality of a data tape based on attributes of the data tape. The system calculates the data quality value using an algorithm based on: (a) a particular data tape error correction value, (b) data tape length value representing a length of data tape traversed during data-processing operations, and (c) a scaling factor. The scaling factor is based on a relationship between the particular data tape error correction value and a rate of degradation of the data tape. The scaling factor may be generated by applying a trained machine learning model to attributes of a data tape. The model generates a scaling factor for a particular data tape based on the attributes of the particular data tape.

Abstract: Techniques are described to perform an automatic reset of a database session to generate an environment that resembles a brand new session without the computational cost of creating a brand new session. In an embodiment, a DBMS receives a request from a client application to execute commands within a session. The DBMS identifies that the end request boundary, the end of the logical work unit for the client application, is reached within the session. The DBMS verifies that the end request boundary is at a resettable point of a session state of the session for the session to be safely reset. If the verification is successful, the DBMS performs a reset of the session to prevent any leakage of application-related session state to the next request.

Abstract: Systems and methods are provided for supporting efficient reconfiguration of an interconnection network having a pre-existing routing. An exemplary method can provide a plurality of switches, a plurality of end nodes, and one or more subnet managers, including a master subnet manager. The method can calculate, via the master subnet manager, a first set of one or more leaf-switch to leaf-switch multipaths. The method can store this first set of one or more leaf-switch to leaf-switch multipaths at a metabase. The method can detect a reconfiguration triggering event, and call a new routing for the interconnection network. Finally, the method can reconfigure the network according to the new routing for the interconnection network.

Abstract: A target set of texts, for training and/or evaluating a text classification model, is augmented using insertions into a base text within the original target set. In an embodiment, an expanded text, including the base text and an insertion word, must satisfy one or more inclusion criteria in order to be added to the target set. The inclusion criteria may require that the expanded text constitutes a successful attack on the classification model, the expanded text has a satisfactory perplexity score, and/or the expanded text is verified as being valid. In an embodiment, if a number of expanded texts added into the target set is below a threshold number, insertions are made into an expanded text (which was generated based on the base text). Inclusion criteria are evaluated against the doubly-expanded text to determine whether to add the doubly-expanded text to the target set.

Abstract: According to one embodiment, a computer-implemented method for dynamically providing a tool bar in a user interface is provided. The method includes determining at least one action that is commonly performed based on data displayed on a current page of a graphical user interface of a communications device, creating a tool bar comprising at least one icon representing the at least one action, associating the tool bar with the current page of the graphical user interface, and providing the tool bar to the communications device for display on the current page of the graphical user interface.

Abstract: A method of efficiently extracting large data sets from a database may include receiving a first result set from a first query executed on one or more data sources. The one or more data sources may use a first schema when the first query was executed. The method may also include receiving a second result set from a second query executed on the one or more data sources. The one or more data sources may use a second schema when the second query was executed. The method may further include generating a view that combines the first result set and the second result set. The view may resolve differences between the first schema and the second schema.

Abstract: Techniques are disclosed for enabling attested end-to-end encryption for transporting data between devices. In one example, a destination device receives a policy profile that includes an origination key and a destination key, and the origination key corresponds to a public transfer key of a source device. The destination device verifies the policy profile based on the destination key corresponding to a public transfer key of the source device. The destination device receives a signed encrypted data encryption key from the source device. The destination device receives encrypted data from the source device. The destination device verifies the signed encrypted data encryption key originated from the source device based on the signed encrypted data key being signed with a private attestation identity key that corresponds to a public attestation identity key of the source device. The destination device decrypts encrypted data using a private transfer key of the destination device.

Abstract: A system and method for use with a cloud computing environment, for determining a cloud score associated with a resource configuration, limits, or shape, for example that of a virtual machine or host provided within the environment. The described approach provides a set of infrastructure workloads, for use in assessing a cloud infrastructure and resources provided thereby, so that a full spectrum of aspects of the cloud infrastructure can be covered by workload testing. The workloads can be used to generate metrics associated with resource usage. The system can then consider one or more metrics that are associated with performance of a particular resource configuration or shape, for example that of a virtual machine or (e.g., bare metal) host hosted by a cloud provider, and determine a score that is indicative of the relative performance of that configuration or shape for a particular workload configuration.

Abstract: In some aspects, a server device may identify one or more services of a cloud infrastructure via a management layer. The server device may determine service information and configuration information for the one or more services. The server device may generate an environment model based at least in part on the service information and the configuration information, the environment model providing information on relationship between one or more components of the cloud infrastructure. The server device may determine one or more threats to the one or more services based at least in part on analyzing the environment model and accessing a threat information database. The server device may generate a threat model that lists the one or more threats to the one or more services. The server device may generate one or more recommendations for the cloud infrastructure based at least on the threat model.

Abstract: Systems and methods for multicast send duplication instead of replication in a high performance computing environment. A method can provide a plurality of switches, a plurality of hosts, the plurality of hosts being interconnected via the plurality of switches, wherein a host of the plurality of hosts comprises a multicast sender node, the sender node comprising a system image generation module and a current message sequence module. The method can organize the plurality of switches into two rails, the two or more rails providing redundant connectivity between the plurality of hosts. The method can send two or more duplicate multicast packets on different rails. Upon a receiving node receiving at least two versions of the same multicast packet, only one will be delivered to the communication stack/clients above the layer that handles the encapsulation header.

Abstract: A method for generating and processing bundled notification request messages includes, at a producer NF, receiving subscription request messages from consumer NFs via one or more SCPs. The method further includes obtaining and storing, from the subscription request messages validated by the producer NF, identities of SCPs within a last N hops of SCPs from the producer NF, N being an integer of at least one. The method further includes detecting an event requiring notifications to a plurality of the consumer NFs. The method further includes identifying, from the SCPs within the last N hops of SCPs from the producer NF, a group of SCPs for which the notifications can be bundled. The method further includes generating a bundled notification request message for the group of SCPs for which the notifications can be bundled. The method further includes transmitting the bundled notification request message to a first-hop SCP in the group of SCPs.

Abstract: Fingerprint inference of software artifacts includes receiving a request including classes, generating request fingerprints from the classes, and querying at least one index with the request fingerprints to identify a matching set of artifact versions. Fingerprint inference further includes obtaining, for each matching artifact version in the matching set of artifact versions, a count of the request fingerprints matching a indexed fingerprint related, in the at least one index, to the artifact version, and selecting a subset of the matching set of artifact versions having a count that is maximal amongst the matching set of artifact versions. Fingerprint inference further includes returning the subset of the matching set of artifact versions.

Abstract: In one aspect, a system receives a request to cluster a set of log records. Responsive to receiving the request, the system identifies at least one dictionary that defines a set of tokens and corresponding token weights and generates, based at least in part on the set of tokens and corresponding token weights, a set of clusters such that each cluster in the set of clusters represents a unique combination of two or more tokens from the dictionary and groups a subset of log records mapped to the unique combination of two or more tokens. The system may then perform one or more automated actions based on at least one cluster in the set of clusters.

Abstract: Techniques for business-to-business (B2B) chat routing are disclosed, including: receiving, by a B2B chatbot during a chat session with a user, user input including a user-supplied business name; performing a business lookup based at least on the user-supplied business name, to obtain a canonical business name and a unique business identifier associated with the canonical business name; performing a customer relationship management (CRM) system lookup based at least on the unique business identifier, to identify a corresponding business account; routing the chat session from the B2B chatbot to a human chat agent assigned to the corresponding business account.

Abstract: Techniques are disclosed for generating machine learning models that are insensitive to drift. A system trains a machine learning model using a divergent training dataset including synthesized data points simulating drift. The system can evaluate the machine learning models in terms of accuracy, latency, efficiency, and other metrics. Based on the evaluation, the system can select a machine learning model least susceptible to drift.

Abstract: Techniques are disclosed herein for continuous hyperparameter tuning with automatic domain weight adjustment based on periodic performance checkpoints. In one aspect, a method is provided that includes initializing a machine learning algorithm with a set of hyperparameter values and obtaining a hyperparameter objective function that is defined at least in part on a plurality of domains of a search space that is associated with the machine learning algorithm. For each trial of a hyperparameter tuning process: running the machine learning algorithm in different domains using the set of hyperparameter values, periodically checking a performance of the machine learning algorithm in the different domains based on the hyperparameter objective function; and continuing hyperparameter tuning with a new set of hyperparameter values after automatically adjusting the domain weights according to a regression status of the different domains.

Abstract: Systems, computer-implemented methods, and computer-readable media for facilitating resource balancing based on resource capacities and resource assignments are disclosed. Electronic communications, received via interfaces, from monitoring devices to identify resource descriptions of resources may be monitored. A resource descriptions data store may be updated to associate each entity of the entities and resource capacities of each resource type of resource types. A first electronic communication, from resource-controlling systems, may be detected. Model data from a model data store may be accessed based on the identified resource descriptions. A first model may be identified based on the model data. A resources assessment corresponding may be generated based on whether a threshold is satisfied based on the first model, a first resource capacity of a first resource type, and the first electronic communication.

Abstract: Techniques are described for transmitting metric data between tenancies. Metric data is gathered for resources within a customer tenancy of a multi-tenant environment. This metric data is sent to a service tenancy of the multi-tenant environment, where the service tenancy is separate from the customer tenancy. The metric data is validated and preprocessed within the service tenancy to make sure that all required fields (such as key-value pairs) are located within the metric data. The preprocessed metric data is then sent to a telemetry service for analysis.

Abstract: Techniques for generating a schema transformation for application data to monitor and manage the application in a runtime environment are disclosed. A system runs an application plugin in a runtime environment to identify data generated by application modules in one or both of an application build process and an application execution process. The application plugin is a software program executed together with the application build process. The application plugin identifies a source schema associated with application data. The application plugin identifies a target schema associated with an analysis program or machine learning model. The application plugin generates a schema transformation to convert application runtime data into a target data set. The system applies the target data set to an analysis program, such as a machine learning model, to generate output analysis data associated with the application.

Abstract: Techniques are described for enabling replication-aware resource management and task management in a cloud infrastructure for cross-region replication. In some embodiments, each replication job is associated with a set of replication-related information. In certain embodiments, the replication-aware resource management allocates resources, using a combination of various resource allocation schemes, to a fleet of replicators to allow the fleet to select replication jobs in a job queue, and perform resource scaling based on monitored performance metrics reported by the fleet. In some embodiments, the replication-aware task management enables replication job selection based on the set of replication-related information to optimize the performance of all cross-region replications in the region.

Abstract: Methods and systems are disclosed for automatic generation of content distribution images that include receiving user input corresponding to a content-distribution operation. The user input may be parsed to identify keywords. Image data corresponding to the keywords can be identified. Image-processing operations may be executed on the image data. Executing a generative adversarial network on the processed image data, which includes: executing a first neural network on the processed-image data to generate first images that correspond to the keywords, the first images generated based on a likelihood that each image of the first images would not be detected as having been generated by the first neural network. A user interface can display the first images with second images that include images that were previously part of content-distribution operations or images that were designated by an entity as being available for content-distribution operations.

Abstract: When a request for accessing a service is received, a user object may be stored in a long-term data store, as well as in a short-term cache. The cache may be divided into a regular cache that stores full versions of the user objects, and a surrogate cache that stores compact versions of the user object. The compact version of the user object may include a field that is derived from the full user object indicating whether a subsequent request for access to a particular service should be granted. After access is granted/denied based on this value in the compact user object, the system can process an update to the full user object offline. This surrogate cache structure may be used to rapidly approve/deny requests, decoupling this procedure from the processing involved with a full user object.

Abstract: A method for processing NF discovery requests using prioritized lists of preferred locations includes maintaining an NF profiles database including NF profiles of producer NFs registered to provide service to other NFs and a preferred locality attribute mappings database including mappings between preferred locality attributes and prioritized lists of preferred locations. The method includes receiving, from an NF, an NF discovery request including query parameters and a preferred locality attribute. The method further includes accessing the preferred locality attribute mappings database using the preferred locality attribute and obtaining a prioritized list of preferred locations corresponding to the preferred locality attribute, accessing the NF profiles database using the query parameters and identifying NF profiles of producer NFs capable of providing a service indicated by the query parameters, and prioritizing the NF profiles according to the prioritized list of preferred locations.

Abstract: A method of detecting anomalous user behavior in a cloud environment includes calculating a first vector that is representative of actions taken during a plurality of previous time intervals; calculating a similarity between the first vector and a second vector that comprises counts of actions taken by the user during a current time interval; comparing the similarity to a baseline threshold to determine whether one or more anomalous actions have occurred; and generating an alert based at least in part on a determination that the one or more anomalous actions have occurred in the cloud environment.

Abstract: Techniques are described for automatically detecting and accommodating state changes in a computer-generated forecast. In one or more embodiments, a representation of a time-series signal is generated within volatile and/or non-volatile storage of a computing device. The representation may be generated in such a way as to approximate the behavior of the time-series signal across one or more seasonal periods. Once generated, a set of one or more state changes within the representation of the time-series signal is identified. Based at least in part on at least one state change in the set of one or more state changes, a subset of values from the sequence of values is selected to train a model. An analytical output is then generated, within volatile and/or non-volatile storage of the computing device, using the trained model.

Abstract: Efficiently implemented herein is a deterministic semantic for property updates by graph queries. Mechanisms of determinism herein ensure data consistency for graph mutation. These mechanisms facilitate optimistic execution of graph access despite a potential data access conflict. This approach may include various combinations of special activities such as detecting potential conflicts during query compile time, applying query transformations to eliminate those conflicts during code generation where possible, and executing updates in an optimistic way that safely fails if determinism cannot be guaranteed. In an embodiment, a computer receives a request to modify a graph. The request to modify the graph is optimistically executed after preparation and according to safety precautions as presented herein. Based on optimistically executing the request, a data access conflict actually occurs and is automatically detected.

Abstract: Techniques for identifying one or more missing fragments within input text are disclosed. A discourse tree (DT) is generated for the input text (IT) received, the IT having any suitable number of sentence fragments. An indication that the IT is likely missing one or more sentence fragments may be identified based on determining that one or more rhetorical relationships of the DT matches one of a set of predefined rhetorical relationships. A query is generated one or more sentence fragments of the IT and executed against a knowledge base to obtain a set of search results. A most-relevance search result can be utilized to identify a set of candidate sentence fragments. A subset of those candidate sentence fragments can be identified based on comparing them to the sentence fragments provided in the IT, each candidate sentence fragment of the subset being implied but excluded from the IT.

Abstract: Routines are used to connect bot queries entered via a bot interface and database queries executed on a database. Each routine is associated with routine configurations, including (a) query attributes associated with bot queries that trigger the routine, (2) a database query executed or to be executed for the routine, and/or (3) display settings for displaying information returned from the database query in a bot response. Each routine is configured to generate an output structured data object (SDO) indicating information returned from the database query and the display settings applicable to the information. The output SDOs from the various routines are transmitted to the bot application via a single API endpoint. The routine configurations are entered by a design user through one or more design user interfaces rendered by an integrative configuration application module.

Abstract: Systems and methods for a virtual network routing gateway that supports address translation for data plane as well as dynamic routing protocols are disclosed herein. The method can include coupling a gateway with a plurality of ports to a network having a plurality of first IP addresses in a private address space, generating a Network Address Translation (“NAT”) function in the gateway, inputting translation information into the NAT function, advertising routes based on the translation information, populating a unified routing table in the gateway based on the plurality of first IP addresses in the private address space and on translated route advertisements, receive an inbound network packet at the gateway, translating an inbound address of the inbound network packet with the NAT function, and delivering the network packet according to the routing table and based on the translated inbound address.

Abstract: Systems and methods for supporting efficient virtualization in a lossless interconnection network. An exemplary method can provide, one or more switches, including at least a leaf switch, a plurality of host channel adapters, wherein each of the host channel adapters comprise at least one virtual function, at least one virtual switch, and at least one physical function, a plurality of hypervisors, and a plurality of virtual machines, wherein each of the plurality of virtual machines are associated with at least one virtual function. The method can arrange the plurality of host channel adapters with one or more of a virtual switch with prepopulated local identifiers (LIDs) architecture or a virtual switch with dynamic LID assignment architecture. The method can assign each virtual switch with a LID. The method can calculate one or more linear forwarding tables based at least upon the LIDs assigned to each of the virtual switches.