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公开(公告)号：US20250117591A1
公开(公告)日：2025-04-10
申请号：US18988114
申请日：2024-12-19
Applicant: Oracle International Corporation
Inventor： Ying XU , Poorya Zaremoodi , Thanh Tien Vu , Cong Duy Vu Hoang , Vladislav Blinov , Yu-Heng Hong , Yakupitiyage Don Thanuja Samodhye Dharmasiri , Vishal Vishnoi , Elias Luqman Jalaluddin , Manish Parekh , Thanh Long Duong , Mark Edward Johnson
IPC: G06F40/35 , G06F40/205 , G06F40/253 , G06N20/00 , H04L51/02
Abstract: Techniques for using logit values for classifying utterances and messages input to chatbot systems in natural language processing. A method can include a chatbot system receiving an utterance generated by a user interacting with the chatbot system. The chatbot system can input the utterance into a machine-learning model including a set of binary classifiers. Each binary classifier of the set of binary classifiers can be associated with a modified logit function. The method can also include the machine-learning model using the modified logit function to generate a set of distance-based logit values for the utterance. The method can also include the machine-learning model applying an enhanced activation function to the set of distance-based logit values to generate a predicted output. The method can also include the chatbot system classifying, based on the predicted output, the utterance as being associated with the particular class.
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公开(公告)号：US11989523B2
公开(公告)日：2024-05-21
申请号：US18113594
申请日：2023-02-23
Applicant: Oracle International Corporation
IPC: G06F17/00 , G06F40/295 , G06F40/30 , H04L67/10
CPC classification number: G06F40/30 , G06F40/295 , H04L67/10
Abstract: The present disclosure relates to chatbot systems, and more particularly, to techniques for obtaining data items for input to a chatbot. In certain embodiments, a chatbot system includes a component that can be invoked by a chatbot in the chatbot system to obtain data items needed by the chatbot. The component can be invoked based on a reference to the component in a dialog flow definition configured for the chatbot. The reference to the component can indicate a composite entity that the component will use to determine how the data items are obtained from a user. The composite entity acts as a container for the data items and may be configured separately from the dialog flow definition of the chatbot. The data items can be obtained based on rules specified in a composite entity definition configured for the composite entity.
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公开(公告)号：US20240126999A1
公开(公告)日：2024-04-18
申请号：US18545621
申请日：2023-12-19
Applicant: Oracle International Corporation
Inventor： Ying Xu , Poorya Zaremoodi , Thanh Tien Vu , Cong Duy Vu Hoang , Vladislav Blinov , Yu-Heng Hong , Yakupitiyage Don Thanuja Samodhye Dharmasiri , Vishal Vishnoi , Elias Luqman Jalaluddin , Manish Parekh , Thanh Long Duong , Mark Edward Johnson
CPC classification number: G06F40/35 , G06N20/00 , H04L51/02 , G06F40/253
Abstract: Techniques for using logit values for classifying utterances and messages input to chatbot systems in natural language processing. A method can include a chatbot system receiving an utterance generated by a user interacting with the chatbot system. The chatbot system can input the utterance into a machine-learning model including a set of binary classifiers. Each binary classifier of the set of binary classifiers can be associated with a modified logit function. The method can also include the machine-learning model using the modified logit function to generate a set of distance-based logit values for the utterance. The method can also include the machine-learning model applying an enhanced activation function to the set of distance-based logit values to generate a predicted output. The method can also include the chatbot system classifying, based on the predicted output, the utterance as being associated with the particular class.
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公开(公告)号：US11657797B2
公开(公告)日：2023-05-23
申请号：US16857047
申请日：2020-04-23
Applicant: Oracle International Corporation
Inventor： Vishal Vishnoi , Xin Xu , Srinivasa Phani Kumar Gadde , Fen Wang , Muruganantham Chinnananchi , Manish Parekh , Stephen Andrew McRitchie , Jae Min John , Crystal C. Pan , Gautam Singaraju , Saba Amsalu Teserra
Abstract: Techniques are described for invoking and switching between chatbots of a chatbot system. In some embodiments, the chatbot system is capable of routing an utterance received while a user is already interacting with a first chatbot in the chatbot system. For instance, the chatbot system may identify a second chatbot based on determining that (i) such an utterance is an invalid input to the first chatbot or (ii) that the first chatbot is attempting to route the utterance to a destination associated with the first chatbot. Identifying the second chatbot can involve computing, using a predictive model, separate confidence scores for the first chatbot and the second chatbot, and then determining that a confidence score for the second chatbot satisfies one or more confidence score thresholds. The utterance is then routed to the second chatbot based on the identifying of the second chatbot.
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公开(公告)号：US11651162B2
公开(公告)日：2023-05-16
申请号：US16857512
申请日：2020-04-24
Applicant: Oracle International Corporation
IPC: G06F17/00 , G06F40/30 , G06F40/295 , H04L67/10
CPC classification number: G06F40/30 , G06F40/295 , H04L67/10
Abstract: The present disclosure relates to chatbot systems, and more particularly, to techniques for obtaining data items for input to a chatbot. In certain embodiments, a chatbot system includes a component that can be invoked by a chatbot in the chatbot system to obtain data items needed by the chatbot. The component can be invoked based on a reference to the component in a dialog flow definition configured for the chatbot. The reference to the component can indicate a composite entity that the component will use to determine how the data items are obtained from a user. The composite entity acts as a container for the data items and may be configured separately from the dialog flow definition of the chatbot. The data items can be obtained based on rules specified in a composite entity definition configured for the composite entity.
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Patent Agency Ranking
公开(公告)号：US20240169155A1
公开(公告)日：2024-05-23
申请号：US18424178
申请日：2024-01-26
Applicant: Oracle International Corporation
Inventor： Vishal Vishnoi , Xin Xu , Elias Luqman Jalaluddin , Srinivasa Phani Kumar Gadde , Crystal C. Pan , Mark Edward Johnson , Thanh Long Duong , Balakota Srinivas Vinnakota , Manish Parekh
IPC: G06F40/295 , G06F40/211 , G06F40/35 , G06F40/56 , G06N5/043
CPC classification number: G06F40/295 , G06F40/211 , G06F40/35 , G06F40/56 , G06N5/043
Abstract: Techniques for automatically switching between chatbot skills in the same domain. In one particular aspect, a method is provided that includes receiving an utterance from a user within a chatbot session, where a current skill context is a first skill and a current group context is a first group, inputting the utterance into a candidate skills model for the first group, obtaining, using the candidate skills model, a ranking of skills within the first group, determining, based on the ranking of skills, a second skill is a highest ranked skill, changing the current skill context of the chatbot session to the second skill, inputting the utterance into a candidate flows model for the second skill, obtaining, using the candidate flows model, a ranking of intents within the second skill that match the utterance, and determining, based on the ranking of intents, an intent that is a highest ranked intent.
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公开(公告)号：US11922123B2
公开(公告)日：2024-03-05
申请号：US17490792
申请日：2021-09-30
Applicant: Oracle International Corporation
Inventor： Vishal Vishnoi , Xin Xu , Elias Luqman Jalaluddin , Srinivasa Phani Kumar Gadde , Crystal C. Pan , Mark Edward Johnson , Thanh Long Duong , Balakota Srinivas Vinnakota , Manish Parekh
IPC: G06F40/295 , G06F40/211 , G06F40/35 , G06F40/56 , G06N5/043
CPC classification number: G06F40/295 , G06F40/211 , G06F40/35 , G06F40/56 , G06N5/043
Abstract: Techniques for automatically switching between chatbot skills in the same domain. In one particular aspect, a method is provided that includes receiving an utterance from a user within a chatbot session, where a current skill context is a first skill and a current group context is a first group, inputting the utterance into a candidate skills model for the first group, obtaining, using the candidate skills model, a ranking of skills within the first group, determining, based on the ranking of skills, a second skill is a highest ranked skill, changing the current skill context of the chatbot session to the second skill, inputting the utterance into a candidate flows model for the second skill, obtaining, using the candidate flows model, a ranking of intents within the second skill that match the utterance, and determining, based on the ranking of intents, an intent that is a highest ranked intent.
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公开(公告)号：US20220171947A1
公开(公告)日：2022-06-02
申请号：US17456916
申请日：2021-11-30
Applicant: Oracle International Corporation
Inventor： Ying Xu , Poorya Zaremoodi , Thanh Tien Vu , Cong Duy Vu Hoang , Vladislav Blinov , Yu-Heng Hong , Yakupitiyage Don Thanuja Samodhye Dharmasiri , Vishal Vishnoi , Elias Luqman Jalaluddin , Manish Parekh , Thanh Long Duong , Mark Edward Johnson
Abstract: Techniques for using logit values for classifying utterances and messages input to chatbot systems in natural language processing. A method can include a chatbot system receiving an utterance generated by a user interacting with the chatbot system. The chatbot system can input the utterance into a machine-learning model including a set of binary classifiers. Each binary classifier of the set of binary classifiers can be associated with a modified logit function. The method can also include the machine-learning model using the modified logit function to generate a set of distance-based logit values for the utterance. The method can also include the machine-learning model applying an enhanced activation function to the set of distance-based logit values to generate a predicted output. The method can also include the chatbot system classifying, based on the predicted output, the utterance as being associated with the particular class.
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公开(公告)号：US20220058347A1
公开(公告)日：2022-02-24
申请号：US17407692
申请日：2021-08-20
Applicant: Oracle International Corporation
Inventor： Gautam Singaraju , Vishal Vishnoi , Manish Parekh , Alexander Wang
Abstract: A chatbot system is configured to execute code to perform determining, by the chatbot system, a classification result for an utterance and one or more anchors each anchor of the one or more anchors corresponding to one or more anchor words of the utterance. For each anchor of the one or more anchors, one or more synthetic utterances are generated, and one or more classification results for the one or more synthetic utterances are determined. A report is generated by the chatbot system comprising a representation of a particular anchor of the one or more anchors, the particular anchor corresponding to a highest confidence value among the one or more anchors. The one or more synthetic utterances may be used to generate a new training dataset for training a machine-learning model. The training dataset may be refined according to a threshold confidence values to filter out datasets for training.
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公开(公告)号：US20200342850A1
公开(公告)日：2020-10-29
申请号：US16857047
申请日：2020-04-23
Applicant: Oracle International Corporation
Inventor： Vishal Vishnoi , Xin Xu , Srinivasa Phani Kumar Gadde , Fen Wang , Muruganantham Chinnananchi , Manish Parekh , Stephen Andrew McRitchie , Jae Min John , Crystal C. Pan , Gautam Singaraju , Saba Amsalu Teserra
Abstract: Techniques are described for invoking and switching between chatbots of a chatbot system. In some embodiments, the chatbot system is capable of routing an utterance received while a user is already interacting with a first chatbot in the chatbot system. For instance, the chatbot system may identify a second chatbot based on determining that (i) such an utterance is an invalid input to the first chatbot or (ii) that the first chatbot is attempting to route the utterance to a destination associated with the first chatbot. Identifying the second chatbot can involve computing, using a predictive model, separate confidence scores for the first chatbot and the second chatbot, and then determining that a confidence score for the second chatbot satisfies one or more confidence score thresholds. The utterance is then routed to the second chatbot based on the identifying of the second chatbot.
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