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公开(公告)号:US20200320497A1
公开(公告)日:2020-10-08
申请号:US16908479
申请日:2020-06-22
Applicant: eBay Inc.
Inventor: Pablo Flores , Barney Mok , Kevin Guo , Carlos Lopez , Jayanth Vasudevan
Abstract: Embodiments of the present disclosure are related to electronic commerce within instant messaging. A system may include a commerce server and an instant messaging server. The instant messaging server is configured to support an instant messaging service with an instant messaging client. The instant messaging server may include an application for supporting further communication in the instant messaging service between the instant messaging client and the commerce server. The method includes first instant messaging a query to an instant messaging client and receiving a response to the query at an application at an instant messaging server. The method further includes second instant messaging query results to the instant messaging client with the query results determined at a commerce server and based on the response.
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公开(公告)号:US20190156177A1
公开(公告)日:2019-05-23
申请号:US15859239
申请日:2017-12-29
Applicant: eBay Inc.
Inventor: Farah Abdallah , Robert Enyedi , Amit Srivastava , Elaine Lee , Braddock Craig Gaskill , Tomer Lancewicki , Xinyu Zhang , Jayanth Vasudevan , Dominique Jean Bouchon
Abstract: Aspect pre-selection techniques using machine learning are described. In one example, an artificial assistant system is configured to implement a chat bot. A user then engages in a first natural-language conversation. As part of this first natural-language conversation, a communication is generated by the chat bot to prompt the user to specify an aspect of a category that is a subject of a first natural-language conversation and user data is received in response. Data that describes this first natural-language conversation is used to train a model using machine learning. Data, is then be received by the chat bot as part of a second natural-language conversation. This data, from the second natural-language conversation, is processed using the model as part of machine learning to generate the second search query to include the aspect of the category automatically and without user intervention.
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公开(公告)号:US11875241B2
公开(公告)日:2024-01-16
申请号:US17462465
申请日:2021-08-31
Applicant: eBay Inc.
Inventor: Farah Abdallah , Robert Enyedi , Amit Srivastava , Elaine Lee , Braddock Craig Gaskill , Tomer Lancewicki , Xinyu Zhang , Jayanth Vasudevan , Dominique Jean Bouchon
IPC: G06N3/006 , G06F16/50 , G06Q30/0601 , G06Q30/0251 , G06F16/9032 , G06Q10/10 , G06F40/30 , G06N20/00 , G06F16/248
CPC classification number: G06N3/006 , G06F16/248 , G06F16/50 , G06F16/90332 , G06F40/30 , G06N20/00 , G06Q10/10 , G06Q30/0256 , G06Q30/0601 , G06Q30/0625
Abstract: Aspect pre-selection techniques using machine learning are described. In one example, an artificial assistant system is configured to implement a chat bot. A user then engages in a first natural-language conversation. As part of this first natural-language conversation, a communication is generated by the chat bot to prompt the user to specify an aspect of a category that is a subject of a first natural-language conversation and user data is received in response. Data that describes this first natural-language conversation is used to train a model using machine learning. Data, is then be received by the chat bot as part of a second natural-language conversation. This data, from the second natural-language conversation, is processed using the model as part of machine learning to generate the second search query to include the aspect of the category automatically and without user intervention.
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公开(公告)号:US20210390365A1
公开(公告)日:2021-12-16
申请号:US17462465
申请日:2021-08-31
Applicant: eBay Inc.
Inventor: Farah Abdallah , Robert Enyedi , Amit Srivastava , Elaine Lee , Braddock Craig Gaskill , Tomer Lancewicki , Xinyu Zhang , Jayanth Vasudevan , Dominique Jean Bouchon
IPC: G06N3/00 , G06F16/50 , G06Q30/06 , G06Q30/02 , G06F16/9032 , G06Q10/10 , G06F40/30 , G06N20/00 , G06F16/248
Abstract: Aspect pre-selection techniques using machine learning are described. In one example, an artificial assistant system is configured to implement a chat bot. A user then engages in a first natural-language conversation. As part of this first natural-language conversation, a communication is generated by the chat bot to prompt the user to specify an aspect of a category that is a subject of a first natural-language conversation and user data is received in response. Data that describes this first natural-language conversation is used to train a model using machine learning. Data, is then be received by the chat bot as part of a second natural-language conversation. This data, from the second natural-language conversation, is processed using the model as part of machine learning to generate the second search query to include the aspect of the category automatically and without user intervention.
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公开(公告)号:US20240095490A1
公开(公告)日:2024-03-21
申请号:US18523674
申请日:2023-11-29
Applicant: eBay Inc.
Inventor: Farah Abdallah , Robert Enyedi , Amit Srivastava , Elaine Lee , Braddock Craig Gaskill , Tomer Lancewicki , Xinyu Zhang , Jayanth Vasudevan , Dominique Jean Bouchon
IPC: G06N3/006 , G06F16/248 , G06F16/50 , G06F16/9032 , G06F40/30 , G06N20/00 , G06Q10/10 , G06Q30/0251 , G06Q30/0601
CPC classification number: G06N3/006 , G06F16/248 , G06F16/50 , G06F16/90332 , G06F40/30 , G06N20/00 , G06Q10/10 , G06Q30/0256 , G06Q30/0601 , G06Q30/0625
Abstract: Aspect pre-selection techniques using machine learning are described. In one example, an artificial assistant system is configured to implement a chat bot. A user then engages in a first natural-language conversation. As part of this first natural-language conversation, a communication is generated by the chat bot to prompt the user to specify an aspect of a category that is a subject of a first natural-language conversation and user data is received in response. Data that describes this first natural-language conversation is used to train a model using machine learning. Data is then received by the chat bot as part of a second natural-language conversation. This data, from the second natural-language conversation, is processed using the model as part of machine learning to generate the second search query to include the aspect of the category automatically and without user intervention.
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公开(公告)号:US11144811B2
公开(公告)日:2021-10-12
申请号:US15859239
申请日:2017-12-29
Applicant: eBay Inc.
Inventor: Farah Abdallah , Robert Enyedi , Amit Srivastava , Elaine Lee , Braddock Craig Gaskill , Tomer Lancewicki , Xinyu Zhang , Jayanth Vasudevan , Dominique Jean Bouchon
IPC: G06F3/048 , G06N3/00 , G06F16/50 , G06Q30/06 , G06Q30/02 , G06F16/9032 , G06Q10/10 , G06F40/30 , G06N20/00 , G06F16/248
Abstract: Aspect pre-selection techniques using machine learning are described. In one example, an artificial assistant system is configured to implement a chat bot. A user then engages in a first natural-language conversation. As part of this first natural-language conversation, a communication is generated by the chat bot to prompt the user to specify an aspect of a category that is a subject of a first natural-language conversation and user data is received in response. Data that describes this first natural-language conversation is used to train a model using machine learning. Data, is then be received by the chat bot as part of a second natural-language conversation. This data, from the second natural-language conversation, is processed using the model as part of machine learning to generate the second search query to include the aspect of the category automatically and without user intervention.
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