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

IPC: G10L15/22 ,  G10L15/18 ,  G10L15/07 ,  G10L15/26 ,  G06F17/30

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：US20190272274A1

公开(公告)日：2019-09-05

申请号：US16290567

申请日：2019-03-01

Applicant: eBay Inc.

Inventor： Ajinkya Gorakhnath Kale ,  Thrivikrama Taula ,  Amit Srivastava

IPC: G06F16/2457 ,  G06F16/28 ,  G06F16/9535

Abstract: Various methods and systems for determining a dominant object of a query and employing the dominant object to provide enhanced search services are discussed. A query is segmented into a set of n_grams. Entity extraction and resolution (EER) methods are employed to determine implicit and explicit aspects for each n_gram. N_grams that include explicit aspects are pruned from the set of n_grams and a pruned set of candidate n_grams is generated from the non-pruned n_grams. Knowledge graphs are employed to generate a ranked list of associated categories for each candidate n_gram. A ranked list of categories associated with the un-segmented query is generated based on knowledge graphs. The candidate n_gram with the highest ranked associated category that is also a highly ranked category associated with the un-segmented query is selected as the dominant object of the query. Enhanced search results are provided based on the determined dominant object.

公开(公告)号：US20180053233A1

公开(公告)日：2018-02-22

申请号：US15238612

申请日：2016-08-16

Applicant: eBay Inc.

Inventor： Amit Srivastava

IPC: G06Q30/06 ,  G06F17/30 ,  G06N99/00

CPC classification number: G06Q30/0625 ,  G06F16/2455 ,  G06F16/951 ,  G06N20/00

Abstract: Methods, systems, and computer programs are presented for adding new features to a network service. A method includes an operation for receiving, by an orchestrator, a sequence specification for a user activity that identifies a type of interaction between a user and the network service, which includes the orchestrator and service servers. The sequence specification includes a sequence of interactions between the orchestrator and a set of service servers to implement the user activity. Further, the method includes operations for configuring the orchestrator to execute the sequence specification when the user activity is detected, for processing user input to detect an intent of the user, and for determining that the intent corresponds to the user activity. The orchestrator executes the sequence specification by invoking the set of service servers, and by causing presentation to the user of a result responsive to the intent of the user.

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

IPC: G10L15/22 ,  G06F16/332 ,  G06F40/35 ,  G10L15/07 ,  G10L15/18 ,  G10L15/26

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：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.

公开(公告)号：US11829375B2

公开(公告)日：2023-11-28

申请号：US17318653

申请日：2021-05-12

Applicant: eBay Inc.

Inventor： Ajinkya Gorakhnath Kale ,  Thrivikrama Taula ,  Amit Srivastava

IPC: G06F16/30 ,  G06F16/2457 ,  G06F16/9535 ,  G06F16/28

CPC classification number: G06F16/24578 ,  G06F16/285 ,  G06F16/9535

Abstract: Various methods and systems for determining a dominant object of a query and employing the dominant object to provide enhanced search services are discussed. A query is segmented into a set of n_grams. Entity extraction and resolution (EER) methods are employed to determine implicit and explicit aspects for each n_gram. N_grams that include explicit aspects are pruned from the set of n_grams and a pruned set of candidate n_grams is generated from the non-pruned n_grams. Knowledge graphs are employed to generate a ranked list of associated categories for each candidate n_gram. A ranked list of categories associated with the un-segmented query is generated based on knowledge graphs. The candidate n_gram with the highest ranked associated category that is also a highly ranked category associated with the un-segmented query is selected as the dominant object of the query. Enhanced search results are provided based on the determined dominant object.

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.

公开(公告)号：US11036746B2

公开(公告)日：2021-06-15

申请号：US16290567

申请日：2019-03-01

Applicant: eBay Inc.

Inventor： Ajinkya Gorakhnath Kale ,  Thrivikrama Taula ,  Amit Srivastava

IPC: G06F16/00 ,  G06F16/2457 ,  G06F16/9535 ,  G06F16/28

Abstract: Various methods and systems for determining a dominant object of a query and employing the dominant object to provide enhanced search services are discussed. A query is segmented into a set of n_grams. Entity extraction and resolution (EER) methods are employed to determine implicit and explicit aspects for each n_gram. N_grams that include explicit aspects are pruned from the set of n_grams and a pruned set of candidate n_grams is generated from the non-pruned n_grams. Knowledge graphs are employed to generate a ranked list of associated categories for each candidate n_gram. A ranked list of categories associated with the un-segmented query is generated based on knowledge graphs. The candidate n_gram with the highest ranked associated category that is also a highly ranked category associated with the un-segmented query is selected as the dominant object of the query. Enhanced search results are provided based on the determined dominant object.

公开(公告)号：US11928428B2

公开(公告)日：2024-03-12

申请号：US18120557

申请日：2023-03-13

Applicant: eBay Inc.

Inventor： Dishan Gupta ,  Ajinkya Gorakhnath Kale ,  Stefan Boyd Schoenmackers ,  Amit Srivastava

IPC: G06F40/274 ,  G06F40/279 ,  G06V30/194

CPC classification number: G06F40/274 ,  G06F40/279 ,  G06V30/194

Abstract: Understanding emojis in the context of online experiences is described. In at least some embodiments, text input is received and a vector representation of the text input is computed. Based on the vector representation, one or more emojis that correspond to the vector representation of the text input are ascertained and a response is formulated that includes at least one of the one or more emojis. In other embodiments, input from a client machine is received. The input includes at least one emoji. A computed vector representation of the emoji is used to look for vector representations of words or phrases that are close to the computed vector representation of the emoji. At least one of the words or phrases is selected and at least one task is performed using the selected word(s) or phrase(s).

公开(公告)号：US11640436B2

公开(公告)日：2023-05-02

申请号：US15681663

申请日：2017-08-21

Applicant: eBay Inc.

Inventor： Ajinkya Gorakhnath Kale ,  Thrivikrama Taula ,  Amit Srivastava ,  Sanjika Hewavitharana

IPC: G06F16/9535 ,  G06N5/02 ,  G06F16/2455 ,  G06F16/33 ,  G06N3/08 ,  G06N5/01

Abstract: A query segmentation system segments a search query into a query segment that identifies search results from items stored on a database. The query segmentation system receives a query string, and the query string comprises a plurality of tokens. A first token and a second token are identified from the plurality of tokens, and a first vector and a second vector associated with the first token and the second token respectively are determined. The query segmentation system determines whether to include the first and second tokens in a single query segment based on the first and second vectors. The single query segment is processed to identify the search results from the database.