Abstract: Exemplary embodiments relate to methods, mediums, and systems for providing group bots that participate in a conversation between multiple participants. Unlike conventional bots that typically interact with users on a one-on-one basis, the group bots may interact collectively with a group, allowing the bots to (among other things) arbitrate decisions for the group, suggest events that all of the members of the group would find agreeable, facilitate conversations by recognizing core language differences between group members and providing translations in response, etc. Furthermore, the group bot may be invoked directly from a group conversation using natural language, and may provide a response directly in the conversation. Because these capabilities are provided directly within a conversation thread, conversation participants can more readily use the bot capabilities without the need to access separate functionality.

Abstract: Techniques for messaging bot controls based on machine-learning user intent detection are described. In one embodiment, an apparatus may comprise a message queue monitoring component operative to monitor a messaging interaction, the messaging interaction exchanged via a messaging system, the messaging interaction involving at least one client device; an interaction processing component operative to determine a user intent for the messaging interaction; and a bot management component operative to determine a messaging bot options configuration for the client device based on the user intent; and send the messaging bot options configuration to the client device. Other embodiments are described and claimed.

Abstract: Exemplary embodiments relate to techniques for suggesting bots or mini-apps in a messaging service that provide capabilities related to an ongoing conversation. A suggestion may be added proactively or reactively. In a reactive scenario, the system may respond to an express request to suggest a response or capability, such as by an explicit command. In the proactive scenario, the messaging service may analyze the messages of the conversation, and may suggest a response or capability based on an intent identified in the messages. Examples of suggestions include starting a poll, adding stickers to the conversation, group coordination and planning capabilities, etc. Suggestions such as these allow a user to make use of various capabilities provided by the messaging service, even if the user does not know that the service exists, or how to invoke it.

Abstract: Techniques for personalized search for bots are described. In one embodiment, an apparatus may comprise a client communication component operative to receive a user service prompt from a user client device at a bot-service system, the user service prompt expressed in natural language and identify two or more filtered bots to the user client device in response to receiving the user service prompt from the user client device; and an interaction processing component operative to determine two or more selected bots of a plurality of bots and determine the two or more filtered bots of the two or more selected bots based on bot relevancy. Other embodiments are described and claimed.

Abstract: Techniques for intent-based search for bots are described. In one embodiment, an apparatus may comprise a bot application interface component operative to receive a plurality of bot capability catalogs for a plurality of bots at a bot-service system, wherein each of the plurality of bot capability catalogs expresses bot capability in natural language for an associated bot; a client communication component operative to receive a user service prompt from a user client device, the user service prompt expressed in natural language; and identify one or more selected bots to the user client device in response to receiving the user service prompt from the user client device; and an interaction processing component operative to determine the one or more selected bots of the plurality of bots by matching the user service prompt against the plurality of bot capability catalogs. Other embodiments are described and claimed.

Abstract: Techniques for messaging bot controls based on machine-learning user intent detection are described. In one embodiment, an apparatus may comprise a message queue monitoring component operative to monitor a messaging interaction, the messaging interaction exchanged via a messaging system, the messaging interaction involving at least one client device; an interaction processing component operative to determine a user intent for the messaging interaction; and a bot management component operative to determine a messaging bot options configuration for the client device based on the user intent; and send the messaging bot options configuration to the client device. Other embodiments are described and claimed.

Abstract: Systems, methods, and non-transitory computer readable media can determine information associated with a web page being accessed by a user operating a computing device. The information associated with the web page can be verified. A messaging interface for exchanging messages with an entity associated with the web page can be provided. The messaging interface can be provided within the web page being accessed.

Abstract: Techniques for reinforcement for bots are described. In one embodiment, an apparatus may comprise a bot application interface component operative to receive a plurality of bot capability catalogs for a plurality of bots at a bot-service system; a client communication component operative to receive a plurality of user service prompts from a plurality of user client devices; and an interaction processing component operative to determine the selected bots of the plurality of bots for each of the plurality of user prompts by matching the plurality of user service prompts against the plurality of bot capability catalogs using a bot capability table generated by a natural-language machine-learning component; record a bot interaction history based on user interactions with the selected bots; and update the natural-language machine-learning component based on the bot interaction history. Other embodiments are described and claimed.

Abstract: Techniques for messaging bot controls based on machine-learning user intent detection are described. In one embodiment, an apparatus may comprise a message queue monitoring component operative to monitor a messaging interaction, the messaging interaction exchanged via a messaging system, the messaging interaction involving at least one client device; an interaction processing component operative to determine a user intent for the messaging interaction; and a bot management component operative to determine a messaging bot options configuration for the client device based on the user intent; and send the messaging bot options configuration to the client device. Other embodiments are described and claimed.

Abstract: Techniques for event-based recommendations for bots are described. In one embodiment, an apparatus may comprise a bot application interface component operative to receive a plurality of agent-event subscriptions for a plurality of agents at a bot-service system; an interaction processing component operative to detect an event associated with a user account, the user account associated with a user client device; and match the event against the plurality of agent-event subscriptions to determine one or more event-response agents; and a client communication component operative to identify the one or more event-response agents to the user client device in response to detecting the event. Other embodiments are described and claimed.

Abstract: Techniques for reinforcement for bots are described. In one embodiment, an apparatus may comprise a bot application interface component operative to receive a plurality of bot capability catalogs for a plurality of bots at a bot-service system; a client communication component operative to receive a plurality of user service prompts from a plurality of user client devices; and an interaction processing component operative to determine the selected bots of the plurality of bots for each of the plurality of user prompts by matching the plurality of user service prompts against the plurality of bot capability catalogs using a bot capability table generated by a natural-language machine-learning component; record a bot interaction history based on user interactions with the selected bots; and update the natural-language machine-learning component based on the bot interaction history. Other embodiments are described and claimed.

Abstract: Techniques for intent-based search for bots are described. In one embodiment, an apparatus may comprise a bot application interface component operative to receive a plurality of bot capability catalogs for a plurality of bots at a bot-service system, wherein each of the plurality of bot capability catalogs expresses bot capability in natural language for an associated bot; a client communication component operative to receive a user service prompt from a user client device, the user service prompt expressed in natural language; and identify one or more selected bots to the user client device in response to receiving the user service prompt from the user client device; and an interaction processing component operative to determine the one or more selected bots of the plurality of bots by matching the user service prompt against the plurality of bot capability catalogs. Other embodiments are described and claimed.

Abstract: Techniques for multiple-user bot application are described. In one embodiment, an apparatus may comprise a messaging component operative on the processor circuit to instantiate a multiple-user interface on a plurality of client devices, wherein the instantiating indicates display of a at least a portion of the multiple-user interface on each of the plurality of client devices; receive a user-interface interaction from a first client device of the plurality of client devices; and update the multiple-user interface on the plurality of client devices based on the user-interface interaction. Other embodiments are described and claimed.

Abstract: Techniques for personalized search for bots are described. In one embodiment, an apparatus may comprise a client communication component operative to receive a user service prompt from a user client device at a bot-service system, the user service prompt expressed in natural language and identify two or more filtered bots to the user client device in response to receiving the user service prompt from the user client device; and an interaction processing component operative to determine two or more selected bots of a plurality of bots and determine the two or more filtered bots of the two or more selected bots based on bot relevancy. Other embodiments are described and claimed.

Abstract: Techniques for messaging bot controls based on machine-learning user intent detection are described. In one embodiment, an apparatus may comprise a message queue monitoring component operative to monitor a messaging interaction, the messaging interaction exchanged via a messaging system, the messaging interaction involving at least one client device; an interaction processing component operative to determine a user intent for the messaging interaction; and a bot management component operative to determine a messaging bot options configuration for the client device based on the user intent; and send the messaging bot options configuration to the client device. Other embodiments are described and claimed.