-
Patent Agency Ranking
公开(公告)号：US11170769B2
公开(公告)日：2021-11-09
申请号：US15926299
申请日：2018-03-20
Applicant: eBay Inc.
Inventor： Stefan Schoenmackers , Amit Srivastava , Lawrence William Colagiovanni , Sanjika Hewavitharana , Ajinkya Gorakhnath Kale , Vinh Khuc
Abstract: Methods, systems, and computer programs are presented for detecting a mission changes in a conversation. A user utterance from a user device is received. The user utterance is part of a conversation with an intelligent assistant. The conversation includes preceding user utterances in pursuit of a first mission. It is determined that the user utterance indicates a mission change from the first mission to a second mission based on an application of a machine-learned model to the user utterance and the preceding user utterances. The machine-learned model has been trained repeatedly with past utterances of other users over a time period, the determining based on a certainty of the indication satisfying a certainty threshold. Responsive to the determining that the user utterance indicates the mission change from the first mission to a second mission, a reply to the user utterance is generated to further the second mission rather than the first mission.
-
公开(公告)号：US20220020375A1
公开(公告)日：2022-01-20
申请号：US17490788
申请日：2021-09-30
Applicant: eBay Inc.
Inventor： Stefan Schoenmackers , Amit Srivastava , Lawrence William Colagiovanni , Sanjika Hewavitharana , Ajinkya Gorakhnath Kale , Vinh Khuc
Abstract: Methods, systems, and computer programs are presented for detecting a mission changes in a conversation. A user utterance from a user device is received. The user utterance is part of a conversation with an intelligent assistant. The conversation includes preceding user utterances in pursuit of a first mission. It is determined that the user utterance indicates a mission change from the first mission to a second mission based on an application of a machine-learned model to the user utterance and the preceding user utterances. The machine-learned model has been trained repeatedly with past utterances of other users over a time period, the determining based on a certainty of the indication satisfying a certainty threshold. Responsive to the determining that the user utterance indicates the mission change from the first mission to a second mission, a reply to the user utterance is generated to further the second mission rather than the first mission.
-
公开(公告)号：US20180268818A1
公开(公告)日：2018-09-20
申请号：US15926299
申请日：2018-03-20
Applicant: eBay Inc.
Inventor： Stefan Schoenmackers , Amit Srivastava , Lawrence William Colagiovanni , Sanjika Hewavitharana , Ajinkya Gorakhnath Kale , Vinh Khuc
CPC classification number: G10L15/22 , G06F16/3329 , G06F17/279 , G10L15/07 , G10L15/1815 , G10L15/265 , G10L2015/228
Abstract: Methods, systems, and computer programs are presented for detecting a mission changes in a conversation. A user utterance from a user device is received. The user utterance is part of a conversation with an intelligent assistant. The conversation includes preceding user utterances in pursuit of a first mission. It is determined that the user utterance indicates a mission change from the first mission to a second mission based on an application of a machine-learned model to the user utterance and the preceding user utterances. The machine-learned model has been trained repeatedly with past utterances of other users over a time period, the determining based on a certainty of the indication satisfying a certainty threshold. Responsive to the determining that the user utterance indicates the mission change from the first mission to a second mission, a reply to the user utterance is generated to further the second mission rather than the first mission.
-
公开(公告)号：US12020701B2
公开(公告)日：2024-06-25
申请号：US17490788
申请日：2021-09-30
Applicant: eBay Inc.
Inventor： Stefan Schoenmackers , Amit Srivastava , Lawrence William Colagiovanni , Sanjika Hewavitharana , Ajinkya Gorakhnath Kale , Vinh Khuc
CPC classification number: G10L15/22 , G06F16/3329 , G06F40/35 , G10L15/07 , G10L15/1815 , G10L15/26 , G10L2015/228
Abstract: Methods, systems, and computer programs are presented for detecting a mission changes in a conversation. A user utterance from a user device is received. The user utterance is part of a conversation with an intelligent assistant. The conversation includes preceding user utterances in pursuit of a first mission. It is determined that the user utterance indicates a mission change from the first mission to a second mission based on an application of a machine-learned model to the user utterance and the preceding user utterances. The machine-learned model has been trained repeatedly with past utterances of other users over a time period, the determining based on a certainty of the indication satisfying a certainty threshold. Responsive to the determining that the user utterance indicates the mission change from the first mission to a second mission, a reply to the user utterance is generated to further the second mission rather than the first mission.
-
公开(公告)号：US20180047071A1
公开(公告)日：2018-02-15
申请号：US15788273
申请日：2017-10-19
Applicant: eBay Inc.
Inventor： David Wei Hsu , Hsu Han Ooi , Samuel Schuler Clark , Stefan Schoenmackers , Igor Tatarinov
IPC: G06Q30/02
CPC classification number: G06Q30/0282
Abstract: Embodiments of the invention can be utilized in multiple ways to assist in generating “predictions” with regards to the expected ratings or rankings of products or services. These predictions can then be used to inform consumers which products or services are expected to be reliable, good values, etc. By using one or more machine learning processes that are trained using product and product review data, embodiments of the invention are able to generate predictions of expected ratings behavior for new products and/or similar products. Further, when the product and product review data is associated with a time at which the data was generated, embodiments of the invention are able to predict how a product or a product's features will be viewed in the future.
-
-
-
-
Search Results
5
records
(took 0.012 seconds)
