Meta Platforms, Inc.

Mikhail Larionov

Jeremy Harrison Goldberg

Chih Shao Lee

Aditya G Bhandarkar

Lei Guang

Seth Garrett Steinberg Rosenberg

Yoram Talmor

Henri Romeo Liriani

Nicolas Andrij Bushak

Zhisheng Huang

Sarah Hum

Jessica Lee

Salahuddin Choudhary

Tsung-Chuan Chen

Yi Xiao

Matthew Robert Anger

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.

Techniques for messaging bot controls based on machine-learning user intent detection

A messaging system receives a message sent by an enterprise to an individual user. The message has an associated message tag describing the content of the message. The messaging system applies a filtering policy to the message. The filtering policy selectively blocks messages sent by enterprises to users. The filtering policy allows the message having the associated tag to pass through the filter even though the message might otherwise violate the filtering policy. The messaging system samples a subset of tagged messages from enterprises and analyzes the messages for compliance with a tagging policy. The messaging system may also train one or more tag models to recognize the correct tags for the messages.

Enforcing messaging policies using tags

Techniques for a messaging agent platform are described. In one embodiment, an apparatus may comprise a intermediary server operative to send a page-scoped identifier to a front-end application, the front-end application associated with an entity, the page-scoped identifier identifying a user account with a messaging system in relation to a representation for the entity within the messaging system; receive a user information request from a contact application at the intermediary server, the contact application associated with the representation for the entity within the messaging system, the user information request for the page-scoped identifier; determine a user access consent setting for the page-scoped identifier for the user account; and send a user information data package to the contact application in response to the user information request when the user access consent setting for the page-scoped identifier indicates user consent. Other embodiments are described and claimed.

Techniques for a messaging agent platform

Techniques for messaging agent messaging interaction are described. In one embodiment, an apparatus may comprise a commerce intermediary server operative to receive a user interface selection of a user-to-commerce message thread on a client device, the user-to-commerce message thread associated with a commerce entity with a messaging system; display a user-to-commerce message thread interface for the user-to-commerce message thread; receive a user-to-commerce message via the user-to-commerce message thread interface for the user-to-commerce message thread; and send the user-to-commerce message to the commerce entity via the messaging system. Other embodiments are described and claimed.

Techniques for messaging agent messaging interactions

Exemplary embodiments relate to techniques for identifying messaging robots, or bots, to surface in response to a request. For example, in order to facilitate increased interaction between a user and a bot, a list of candidate bots that the user is likely to be interested in may be surfaced to the user in response to a search for a bot or a request that a bot perform a particular task. Identifying the bots may be accomplished by generating a list of candidate bots and filtering the list based on filtering metrics. Then, the remaining bots may be ranked based on ranking metrics, and the top bots in the ranking may be returned. In some embodiments, two sets of ranks may calculated: one for retention rate, and another rank for the number of messages sent and received by the bots.

Methods and systems for ranking messaging bots

Growing community of inventors

Palo Alto, CA, United States of America

Mikhail Larionov