- Menlo Park CA, US Jeremy Harrison Goldberg - San Francisco CA, US Kemal El Moujahid - Mountain View CA, US Yoram Talmor - Cupertino CA, US Chih Shao Lee - Sunnyvale CA, US Seyed Ahmad Anvari - Mountain View CA, US Michael Allen Anvari - Mountain View CA, US Haotian Zhang - Fremont CA, US Matthew Robert Anger - San Francisco CA, US Nicolas Andrij Bushak - San Francisco CA, US Salahuddin Choudhary - Palo Alto CA, US Christopher Bing Chen - San Francisco CA, US
International Classification:
G06F 17/30 G06Q 50/00 G06F 3/048
Abstract:
Techniques for ranking of selected bots are described. In one embodiment, for example, an apparatus may comprise a client front-end component operative to receive a bot contact display prompt from a client device; and send an ordered bot contact list to the client device; a bot contact list component operative to retrieve a bot contact list from a selection component, the bot contact list comprising a plurality of bot contacts; and a contact ranking component operative to determine a ranking weight for each of the plurality of bot contacts; and generate the ordered bot contact list by ordering the bot contact list based on the ranking weight. Other embodiments are described and claimed.
- Menlo Park CA, US Tsung-Chuan Chen - Palo Alto CA, US Chih Shao Lee - Sunnyvale CA, US Mikhail Larionov - Palo Alto CA, US
International Classification:
G06F 17/30 H04L 12/58
Abstract:
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.
Techniques For Messaging Bot Controls Based On Machine-Learning User Intent Detection
- Menlo Park CA, US Sarah Hum - San Francisco CA, US Mikhail Larionov - Palo Alto CA, US Chih Shao Lee - Sunnyvale CA, US Lei Guang - Bellevue WA, US Zhisheng Huang - Sunnyvale CA, US Henri Romeo Liriani - San Francisco CA, US
International Classification:
H04L 12/58 G06N 99/00 H04L 29/08
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.