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 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: A server sends, to an electronic device of a first user, a data structure that includes a hierarchical interaction tree having a plurality of interaction nodes. The server then receives, from the electronic device of the first user, a first message, wherein the first message from the electronic device of the first user is selected from a set of predefined first-reply messages. Each first-reply message of the set of predefined first-reply messages corresponds to a distinct interaction node of the hierarchical interaction tree.

Abstract: An electronic device of a second user receives, from a first user, a first message. Subsequent to receiving the first message, the electronic device sends, to the first user, a second message responsive to the first message, wherein the second message is selected from a set of predefined first-reply messages. The set of predefined first-reply messages is based on first-reply factors for the second user, including content from one or more messages between the first user and the second user, and including one or more of: relationship characteristics between the first user and the second user, information provided by the first user and/or the second user to a social network, profile characteristics of the first user and/or the second user, environmental characteristics of the first user and/or the second user, and/or technical characteristics of the electronic device of the first user and/or the second user.

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 presenting and targeting media in communications services. Media, such as live events, updates on a topic of interest, or digests of news sites or other content providers may be surfaced to a user in a number of ways; for example, an article view relating to the topic, a messaging view showing message threads, a media view showing interesting pieces of media, or in an active conversation based on analysis of a conversation and trending topics, such as news events. A system may suggest recipients that may be interested in discussing the content. The recipients may be presented in a ranked order based, for example, on an affinity or relationship of the recipients to a publisher of the content. Publishers may add or remove topics, and may set an end-time at which updates cease. The updates may be presented in a messaging thread.

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: A server sends, to an electronic device of a first user, a data structure that includes a hierarchical interaction tree having a plurality of interaction nodes. The server then receives, from the electronic device of the first user, a first message, wherein the first message from the electronic device of the first user is selected from a set of predefined first-reply messages. Each first-reply message of the set of predefined first-reply messages corresponds to a distinct interaction node of the hierarchical interaction tree.

Abstract: An electronic device of a second user receives, from a first user, a first message. Subsequent to receiving the first message, the electronic device sends, to the first user, a second message responsive to the first message, wherein the second message is selected from a set of predefined first-reply messages. The set of predefined first-reply messages is based on first-reply factors for the second user, including content from one or more messages between the first user and the second user, and including one or more of: relationship characteristics between the first user and the second user, information provided by the first user and/or the second user to a social network, profile characteristics of the first user and/or the second user, environmental characteristics of the first user and/or the second user, and/or technical characteristics of the electronic device of the first user and/or the second user.