Abstract: Systems for processing queries may first determine correspondence between the parameters of the query and a set of existing data entries, a set of previous queries that have been received, or both the existing data entries and the previous queries. If the query parameters do not correspond to the data entries or pervious queries, correspondence is determined between the query parameters and group data that associates at least a subset the query parameters with a particular group that may generate a response to the query. The same group or the generated response may be used when similar queries are received. If the group transmits the query to a different group or if negative user feedback is received, the group data may be modified to indicate the different group or to remove the association with the initial group that received the query.

Abstract: A document is divided into sections based on a characteristic of the text in the document. Characteristics may include specific characters such as paragraph breaks or selected punctuation, the topics or categories of the text, or a quantity of text in each section. Each section of the document may be represented by an embedding vector in a semantic embedding space. Values are determined based on the text in each section and the semantic characteristics of each section, such as word order, capitalization, punctuation, and word meaning. When a query is received, a vector value representing the query is determined based on the text and semantic characteristics of the query. Based on the similarity between the values determined for the query and those determined for the sections of a document, the specific section of a potentially large document that most closely matches the query is determined and included in a response.

Abstract: Systems for processing queries may first determine correspondence between the parameters of the query and a set of existing data entries, a set of previous queries that have been received, or both the existing data entries and the previous queries. If the query parameters do not correspond to the data entries or pervious queries, correspondence is determined between the query parameters and group data that associates at least a subset the query parameters with a particular group that may generate a response to the query. The same group or the generated response may be used when similar queries are received. If the group transmits the query to a different group or if negative user feedback is received, the group data may be modified to indicate the different group or to remove the association with the initial group that received the query.

Abstract: A system creates and searches knowledge base (KB) articles inside an organization while supporting operation as a SaaS (Software as-a-Service) across a plurality of organizations. The system implements a real-time online learning-to-rank (L2R) algorithm for learning relevance scoring that is customized to each organization. This algorithm incorporates rich lexical features using a query similarity kernel. A scoring function includes a pairwise static module, which may be trained off-line using training data, and a lexical adaptive module, which is trained on-line based on user feedback. The scoring function makes the system easy to deploy, modify, and suitable for handling events that naturally happen over the lifecycle of any KB deployment, without manual training.

Abstract: An organization has or uses an SLA system that selects a service-level agreement (SLA) that should apply to a given user request. The SLA system then can monitor the state of the ticket created based on the user request and provide messages or other feedback to the agent to aid the agent in meeting any performance goals associated with the SLA. The SLA system can determine the SLA to associate with a given user request by inferring a type of the request and selecting the SLA based on the type, or by using a model to directly associate an SLA to a given user request, without the need to infer an intermediate type for the user request, which eliminates the need for administrators to create and maintain metadata to guide the association between types and SLAs.

Abstract: A system stores resources such as text articles, videos, and so forth for an organization. During operation, the system receives a query and provides a response. During initial use of the system, there is little or no historical data available to help determine which resource is most relevant to a particular query. In this “cold-start” situation, the system determines attributes associated with a user account of the user making the query. The query is used to search a data store and retrieve a set of resources based on a term match with the query and to find the resources which correspond to the attributes of the user account. This allows the system to provide simplified output that is more likely to be relevant to that particular user in the “cold-start” situation.

Abstract: A system stores resources such as text articles, videos, and so forth for an organization. During operation, the system receives a query and provides a response. During initial use of the system, there is little or no historical data available to help determine which resource is most relevant to a particular query. In this “cold-start” situation, the system determines attributes associated with a user account of the user making the query. The query is used to search a data store and retrieve a set of resources based on a term match with the query and to find the resources which correspond to the attributes of the user account. This allows the system to provide simplified output that is more likely to be relevant to that particular user in the “cold-start” situation.

Abstract: Systems for processing queries may first determine correspondence between the parameters of the query and a set of existing data entries, a set of previous queries that have been received, or both the existing data entries and the previous queries. If the query parameters do not correspond to the data entries or pervious queries, correspondence is determined between the query parameters and group data that associates at least a subset the query parameters with a particular group that may generate a response to the query. The same group or the generated response may be used when similar queries are received. If the group transmits the query to a different group or if negative user feedback is received, the group data may be modified to indicate the different group or to remove the association with the initial group that received the query.

Abstract: Systems for processing queries may first determine correspondence between the parameters of the query and a set of existing data entries, a set of previous queries that have been received, or both the existing data entries and the previous queries. If the query parameters do not correspond to the data entries or pervious queries, correspondence is determined between the query parameters and group data that associates at least a subset the query parameters with a particular group that may generate a response to the query. The same group or the generated response may be used when similar queries are received. If the group transmits the query to a different group or if negative user feedback is received, the group data may be modified to indicate the different group or to remove the association with the initial group that received the query.

Abstract: Systems and methods for determining whether a data entry has deprecated may receive a query from a user device and provide a data entry responsive to the query. If user feedback associated with the response indicates that the response resolved the query, confirmation data that associates the data entry with the query parameters is generated. If the user feedback indicates that the response did not resolve the query, existing confirmation data is accessed to determine whether a previous association between the data entry and the parameters of the query was generated. If correspondence between the confirmation data and the query and response is determined, a notification indicating the deprecation of the data entry is generated and the data entry may be suppressed from future output.

Abstract: A system dynamically routes queries from an organization for processing. An incoming query is classified using a base model to determine a canonical group. The query is routed based on the canonical group. Responsive to the query, response data is then provided to the user device. Event data about the query, the routing, and the response data is used to train a first model that is used to determine subsequent routing. When a threshold is reached with respect to the available event data, a second model is trained using the event data. Processing of subsequent queries using the second model results in reduced demand for computer resources and reduces response times. The second model may be retrained on a schedule, or upon occurrence of a trigger event, such as an addition or removal of a canonical group.

Abstract: A system for processing queries from a user device may first generate an augmented query by determining weight values and synonyms for at least a portion of the parameters in the query, and adding or removing one or more query parameters. Correspondence between the augmented query and an existing set of data entries may be used to determine a subset of data entries that may be responsive to the query. Correspondence may then be determined between the augmented query and previous queries that were addressed by the subset of data entries, to determine a particular previous query having the greatest correspondence with the augmented query. The data entry associated with the particular previous query may be used to generate a response to the query received from the user device.

Abstract: An example system may include a first device connected over respective communications interfaces to a plurality of second devices. The first device may establish respective remote terminals between the first device and one or more second devices. Establishing the respective remote terminals may indicate that the devices are in an online state. The first device may periodically update respective heartbeat files on the second devices. A respective second device may detect that a pre-determined time period has elapsed since the heartbeat file was updated. The respective second device may determine that a respective remote terminal between the first device and the respective second device has been terminated. Determining that the remote terminal has been terminated may indicate that the device is in an offline state. The respective second device may reset itself so as to transition the respective second device from the offline state to the online state.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for performing tests on mobile devices. In one aspect, a power distribution system includes a set of mobile devices and a computer that manages the execution of a test using the set of mobile devices. The computer can include one or more data communication ports. The system can also include one or more Universal Serial Bus (USB) hubs connected to the mobile devices using USB cables. Each mobile device can be connected to one of the one or more USB hubs. The system can also include one or more USB charging hubs connected between each data communication port of the computer and at least one of the one or more USB hubs. The system can also include a power supply connected between a power source and each of the one or more USB hubs.

Abstract: Various embodiments provide an automated testing analysis tool, termed a “pre-release analysis tool”, that tests applications for functional and nonfunctional requirements. In at least some embodiments, the pre-release analysis tool can perform both static analysis and dynamic analysis on an application. A report module can provide rich feedback, including actionable feedback, to an application developer in order to enable the developer to make their applications more secure, reliable, efficient, and performant. Actionable feedback can include feedback that suggests various remedial measures that an application developer may put in place in order to improve their applications. Application analysis can be performed in various different categories with actionable feedback provided in each. These different categories can include, by way of example and not limitation, application crashes, performance, security, usability, application statistics, code warnings, localization issues, and network issues.

Abstract: Methods and apparatus are provided for providing testing as a service. A loading computing device can receive a request to restore a testing computing device to a known software configuration. The loading computing device, after receiving the request to restore the testing computing device, can restore the testing computing device by at least: obtaining a software image storing the known software configuration, where the software image includes security-context data having security contexts associated with the plurality of software components, and where a particular security context can have an identity, a role, and a domain or type; storing at least part of the obtained software image onto the testing computing device, and after storing at least part of the obtained software image onto the testing computing device, setting security contexts for the obtained software image stored on the testing computing device using the security-context data.

Abstract: A data center rack includes a housing, at least one wireless access point (AP) mounted within the housing and wirelessly connectable to a network switch external to the housing, and at least one tray including a plurality of mobile device power connections to provide power to a plurality of mobile devices.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for performing tests on mobile devices. In one aspect, a power distribution system includes a set of mobile devices and a computer that manages the execution of a test using the set of mobile devices. The computer can include one or more data communication ports. The system can also include one or more Universal Serial Bus (USB) hubs connected to the mobile devices using USB cables. Each mobile device can be connected to one of the one or more USB hubs. The system can also include one or more USB charging hubs connected between each data communication port of the computer and at least one of the one or more USB hubs. The system can also include a power supply connected between a power source and each of the one or more USB hubs.

Abstract: Various embodiments provide an automated testing analysis tool, termed a “pre-release analysis tool”, that tests applications for functional and nonfunctional requirements. In at least some embodiments, the pre-release analysis tool can perform both static analysis and dynamic analysis on an application. A report module can provide rich feedback, including actionable feedback, to an application developer in order to enable the developer to make their applications more secure, reliable, efficient, and performant. Actionable feedback can include feedback that suggests various remedial measures that an application developer may put in place in order to improve their applications. Application analysis can be performed in various different categories with actionable feedback provided in each. These different categories can include, by way of example and not limitation, application crashes, performance, security, usability, application statistics, code warnings, localization issues, and network issues.

Abstract: An example system may include a first device connected over respective communications interfaces to a plurality of second devices. The first device may establish respective remote terminals between the first device and one or more second devices. Establishing the respective remote terminals may indicate that the devices are in an online state. The first device may periodically update respective heartbeat files on the second devices. A respective second device may detect that a pre-determined time period has elapsed since the heartbeat file was updated. The respective second device may determine that a respective remote terminal between the first device and the respective second device has been terminated. Determining that the remote terminal has been terminated may indicate that the device is in an offline state. The respective second device may reset itself so as to transition the respective second device from the offline state to the online state.