Abstract: The present disclosure relates to polymer compositions, articles formed from polymer compositions, methods of making polymer compositions, and methods of making articles including polymer compositions. In at least one embodiment, a composition includes: (1) an ethylene polymer, (2) a vinyl alcohol polymer or a polyamide, and (3) a polar polymer or a grafted polyolefin. A composition of the present disclosure may further include a polypropylene polymer. A polar polymer may be an ethylene-acrylic-acid-copolymer, ethylene acrylate copolymer, a polyvinyl acetate, or combination(s) thereof. In at least one embodiment, a film includes a composition having: (1) an ethylene polymer, (2) a vinyl alcohol polymer or a polyamide, and (3) a polar polymer or a grafted polyolefin.

Abstract: A system for operating and/or lubricating a plurality of valves. The system includes at least first and second control units, each of which is associated with a respective valve. Each control unit includes a hydraulic pressure inlet, a hydraulic pressure outlet, a hydraulic pressure line connected between the hydraulic pressure inlet and the hydraulic pressure outlet, and a hydraulic port which is connectable to the valve. The hydraulic pressure inlet of the first control unit is connectable to a hydraulic pressure source and the hydraulic pressure outlet of the first control unit is connectable to the hydraulic pressure inlet of the second control unit. In operation, the control unit is operable to selectively communicate hydraulic pressure from the hydraulic pressure line to the hydraulic port.

Abstract: A multi-tenant system performs custom configuration of a tenant-specific chatbot to process and act upon natural language requests. The multi-tenant system configures the tenant-specific chatbots without requiring tenant-specific training. The multi-tenant system providing a user interface for configuring a tenant-specific set of permitted actions. The multi-tenant system determines a set of example phrases for each of the selected permitted actions. The multi-tenant system receives a natural language request from a user and identifies the action that the user wants to perform. The multi-tenant system uses a neural network to compare the natural language request with example phrases to identify an example phrase that matches the natural language request. The multi-tenant system performs the action corresponding to the matching example phrase.

Abstract: A method for associating a team with a meeting for prospective meeting attendees includes training a machine-learning algorithm to determine a match metric between a group of meeting attendees and a plurality of teams; in response to receiving a meeting invitation for a meeting, determining, by the processor, using the trained machine-learning algorithm, a match metric for each of the plurality of teams in a team system; in response to determining that the match metric for each of the plurality of teams is below a threshold value, creating, by the processor, a new team; associating, by the processor, the new team with the meeting for prospective meeting attendees; and sending, to the prospective meeting attendees, a link to the new team.

Abstract: A method for associating a team with a meeting for prospective meeting includes receiving a meeting invitation comprising first information, wherein the first information comprises data identifying the prospective meeting attendees, receiving second information for a plurality of teams, wherein the second information comprises data identifying members for each one of the plurality of teams, comparing the first information with the second information to determine a match metric for each one of the plurality of teams, and determining a matching team from the plurality of teams for which the match metric is above a match threshold value. The method further includes, in response to determining that the match metric is below the match threshold value computed for each one of the plurality of teams, creating a new team, and associating one of the matching team or the new team with the meeting for prospective meeting attendees.

Abstract: Approaches to using unstructured input to update heterogeneous data stores include receiving unstructured text input, receiving a template for interpreting the unstructured text input, identifying, using an entity classifier, entities in the unstructured text input, identifying one or more potential parent entities from the identified entities based on the template, receiving a selection of a parent entity from the one or more potential parent entities, identifying one or more potential child entities from the identified entities based on the template and the selected parent entity, receiving a selection of a child entity from the one or more potential child entities, identifying an action item in the unstructured text input based on the identified entities and the template, determining, using an intent classifier, an intent of the action item, and updating a data store based on the determined intent, the identified entities, and the selected child entity.

Abstract: A method for natural language processing includes receiving, by one or more processors, an unstructured text input. An entity classifier is used to identify entities in the unstructured text input. The identifying the entities includes generating, using a plurality of sub-classifiers of a hierarchical neural network classifier of the entity classifier, a plurality of lower-level entity identifications associated with the unstructured text input. The identifying the entities further includes generating, using a combiner of the hierarchical neural network classifier, a plurality of higher-level entity identifications associated with the unstructured text input based on the plurality of lower-level entity identifications. Identified entities are provided based on the plurality of higher-level entity identifications.

Abstract: The present disclosure is directed techniques for executing a task or service using a virtual agent.

Abstract: The present disclosure is directed techniques for executing a task or service using a virtual agent. A method includes: defining a plurality of intents; conducting a first tier of machine learning analysis to compare a received input string with a first subset of training phrases associated with the plurality of intents to extract one or more parameters of the received input string; conducting a second tier of machine learning analysis to compare an output of the first tier of machine learning analysis with a second subset of training phrases associated with the plurality of intents, wherein the comparison is used to generate respective similarity scores indicating whether the received input string matches one or more of the second subset of training phrases; selecting an intent from among the plurality of intents based on the respective similarity scores; and executing an action associated with the selected intent.

Abstract: A method for associating a team with a meeting for prospective meeting includes receiving a meeting invitation comprising first information, wherein the first information comprises data identifying the prospective meeting attendees, receiving second information for a plurality of teams, wherein the second information comprises data identifying members for each one of the plurality of teams, comparing the first information with the second information to determine a match metric for each one of the plurality of teams, and determining a matching team from the plurality of teams for which the match metric is above a match threshold value. The method further includes, in response to determining that the match metric is below the match threshold value computed for each one of the plurality of teams, creating a new team, and associating one of the matching team or the new team with the meeting for prospective meeting attendees.

Abstract: Described herein is a method, system, and non-transitory computer readable medium for updating fields in records. Initially, fields are displayed according to how frequently the fields are updated. One of the fields is selected and then records of a record type including the selected field are displayed. One of the records is selected and a form is displayed that enables a user to update the value stored in the selected field of the selected record.

Abstract: Approaches to using unstructured input to update heterogeneous data stores include receiving unstructured text input, receiving a template for interpreting the unstructured text input, identifying, using an entity classifier, entities in the unstructured text input, identifying one or more potential parent entities from the identified entities based on the template, receiving a selection of a parent entity from the one or more potential parent entities, identifying one or more potential child entities from the identified entities based on the template and the selected parent entity, receiving a selection of a child entity from the one or more potential child entities, identifying an action item in the unstructured text input based on the identified entities and the template, determining, using an intent classifier, an intent of the action item, and updating a data store based on the determined intent, the identified entities, and the selected child entity.

Abstract: A multi-tenant system performs custom configuration of a tenant-specific chatbot to process and act upon natural language requests. The multi-tenant system configures the tenant-specific chatbots without requiring tenant-specific training. The multi-tenant system providing a user interface for configuring a tenant-specific set of permitted actions. The multi-tenant system determines a set of example phrases for each of the selected permitted actions. The multi-tenant system receives a natural language request from a user and identifies the action that the user wants to perform. The multi-tenant system uses a neural network to compare the natural language request with example phrases to identify an example phrase that matches the natural language request. The multi-tenant system performs the action corresponding to the matching example phrase.

Abstract: Approaches to using unstructured input to update heterogeneous data stores include receiving unstructured text input, receiving a template for interpreting the unstructured text input, identifying, using an entity classifier, entities in the unstructured text input, identifying one or more potential parent entities from the identified entities based on the template, receiving a selection of a parent entity from the one or more potential parent entities, identifying one or more potential child entities from the identified entities based on the template and the selected parent entity, receiving a selection of a child entity from the one or more potential child entities, identifying an action item in the unstructured text input based on the identified entities and the template, determining, using an intent classifier, an intent of the action item, and updating a data store based on the determined intent, the identified entities, and the selected child entity.

Abstract: For a database system accessible by one or more users, a neural network model and related method are provided that allow a user of the database system to provide unstructured input in the form of a verbal or textual narrative or utterance that expresses the information in a language and manner that is more comfortable for the user. A portion of the narrative or utterance may relate to one or action items that the user intends to be taken with respect to the database system, such as creating, updating, modifying, or deleting a database item (e.g., contact, calendar item, deal, etc.). The neural model processes the unstructured input (narrative or utterance) and determines or classifies the intent with respect to the action item for the database.

Abstract: Approaches to using unstructured input to update heterogeneous data stores include receiving unstructured text input, receiving a template for interpreting the unstructured text input, identifying, using an entity classifier, entities in the unstructured text input, identifying one or more potential parent entities from the identified entities based on the template, receiving a selection of a parent entity from the one or more potential parent entities, identifying one or more potential child entities from the identified entities based on the template and the selected parent entity, receiving a selection of a child entity from the one or more potential child entities, identifying an action item in the unstructured text input based on the identified entities and the template, determining, using an intent classifier, an intent of the action item, and updating a data store based on the determined intent, the identified entities, and the selected child entity.

Abstract: A method for natural language processing includes receiving, by one or more processors, an unstructured text input. An entity classifier is used to identify entities in the unstructured text input. The identifying the entities includes generating, using a plurality of sub-classifiers of a hierarchical neural network classifier of the entity classifier, a plurality of lower-level entity identifications associated with the unstructured text input. The identifying the entities further includes generating, using a combiner of the hierarchical neural network classifier, a plurality of higher-level entity identifications associated with the unstructured text input based on the plurality of lower-level entity identifications. Identified entities are provided based on the plurality of higher-level entity identifications.

Abstract: Example systems and methods for integrating a primary data store (e.g., a source-of-truth relational database management system) and a secondary data store (e.g., external cache) are described. The approach implements a modified read-through/write-through data access pattern that integrates read and write flows in order to support high-concurrency environments while maintaining immediate consistency between stores. Writes are handled using a three-phase flow that avoids concurrency-related race conditions and the need to block in the secondary store in order to maintain cross-store consistency. Reads are never dirty and will repair the secondary store as needed without conflicting with repairs that may have been initiated by other sessions.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for detecting security exposures of Voice over Internet Protocol (VOIP) devices. One of the methods includes obtaining data identifying a source Internet Protocol (IP) address associated with a communication device that has been provisioned with configuration files for VOIP services; determining that a VOIP phone configuration interface is exposed over an untrusted network at the source IP address; and determining that the communication device associated with the source IP address has a security exposure based at least in part on determining that the VOIP phone configuration interface is exposed over the untrusted network at the source IP address.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for detecting security exposures of Voice over Internet Protocol (VOIP) devices. One of the methods includes obtaining data identifying a source Internet Protocol (IP) address associated with a communication device that has been provisioned with configuration files for VOIP services; determining that a VOIP phone configuration interface is exposed over an untrusted network at the source IP address; and determining that the communication device associated with the source IP address has a security exposure based at least in part on determining that the VOIP phone configuration interface is exposed over the untrusted network at the source IP address.