公开(公告)号：US20240169153A1

公开(公告)日：2024-05-23

申请号：US18428817

申请日：2024-01-31

Applicant: Oracle International Corporation

Inventor： Crystal C. Pan ,  Guatam Singaraju ,  Vishal Vishnoi ,  Srinivasa Phani Kumar Gadde

IPC: G06F40/284 ,  G06F18/23213 ,  G06F18/24 ,  G06F40/216 ,  G06F40/35 ,  G06N20/00 ,  H04L51/02

CPC classification number: G06F40/284 ,  G06F18/23213 ,  G06F18/24 ,  G06F40/216 ,  G06F40/35 ,  G06N20/00 ,  H04L51/02

Abstract: Techniques are described to determine whether an input utterance is unrelated to a set of skill bots associated with a master bot. In some embodiments, a system described herein includes a training system and a master bot. The training system trains a classifier of the master bot. The training includes accessing training utterances associated with the skill bots and generating training feature vectors from the training utterances. The training further includes generating multiple set representations of the training feature vectors, where each set representation corresponds to a subset of the training feature vectors, and configuring the classifier with the set representations. The master bot accesses an input utterance and generates an input feature vector. The master bot uses the classifier to compare the input feature vector to the multiple set representations so as to determine whether the input feature falls outside and, thus, cannot be handled by the skill bots.

公开(公告)号：US20230376696A1

公开(公告)日：2023-11-23

申请号：US18364298

申请日：2023-08-02

Applicant: Oracle International Corporation

Inventor： Thanh Long Duong ,  Mark Edward Johnson ,  Vishal Vishnoi ,  Crystal C. Pan ,  Vladislav Blinov ,  Cong Duy Vu Hoang ,  Elias Luqman Jalaluddin ,  Duy Vu ,  Balakota Srinivas Vinnakota

IPC: G06F40/30 ,  G06N20/00 ,  G06F40/289 ,  H04L51/02

CPC classification number: G06F40/30 ,  G06N20/00 ,  G06F40/289 ,  H04L51/02 ,  G06F40/205

Abstract: The present disclosure relates to techniques for identifying out-of-domain utterances. One particular technique includes receiving an utterance and a target domain of a chatbot, generating a sentence embedding for the utterance, obtaining an embedding representation for each cluster of in-domain utterances associated with the target domain, predicting, using a metric learning model, a first probability that the utterance belongs to the target domain based on a similarity or difference between the sentence embedding and each embedding representation for each cluster, predicting, using an outlier detection model, a second probability that the utterance belongs to the target domain based on a determined distance or density deviation between the sentence embedding and embedding representations for neighboring clusters, evaluating the first probability and the second probability to determine a final probability, and classifying the utterance as in-domain or out-of-domain for the chatbot based on the final probability.

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

IPC: G06F17/00 ,  G10L13/08 ,  G06N5/04 ,  G06N20/00

CPC classification number: G10L13/08 ,  G06N5/04 ,  G06N20/00

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.

公开(公告)号：US12299402B2

公开(公告)日：2025-05-13

申请号：US18659606

申请日：2024-05-09

Applicant: Oracle International Corporation

Inventor： Thanh Long Duong ,  Mark Edward Johnson ,  Vishal Vishnoi ,  Crystal C. Pan ,  Vladislav Blinov ,  Cong Duy Vu Hoang ,  Elias Luqman Jalaluddin ,  Duy Vu ,  Balakota Srinivas Vinnakota

IPC: G06F40/30 ,  G06F40/205 ,  G06F40/289 ,  G06N20/00 ,  H04L51/02

Abstract: The present disclosure relates to techniques for identifying out-of-domain utterances. One particular technique includes receiving an utterance and a target domain of a chatbot, generating a sentence embedding for the utterance, obtaining an embedding representation for each cluster of in-domain utterances associated with the target domain, predicting, using a metric learning model, a first probability that the utterance belongs to the target domain based on a similarity or difference between the sentence embedding and each embedding representation for each cluster, predicting, using an outlier detection model, a second probability that the utterance belongs to the target domain based on a determined distance or density deviation between the sentence embedding and embedding representations for neighboring clusters, evaluating the first probability and the second probability to determine a final probability, and classifying the utterance as in-domain or out-of-domain for the chatbot based on the final probability.

公开(公告)号：US12249314B2

公开(公告)日：2025-03-11

申请号：US18136745

申请日：2023-04-19

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

IPC: G06F17/00 ,  G06N5/04 ,  G06N20/00 ,  G10L13/08

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.

公开(公告)号：US11928430B2

公开(公告)日：2024-03-12

申请号：US17017076

申请日：2020-09-10

Applicant: Oracle International Corporation

Inventor： Crystal C. Pan ,  Gautam Singaraju ,  Vishal Vishnoi ,  Srinivasa Phani Kumar Gadde

IPC: G06F40/284 ,  G06F18/23213 ,  G06F18/24 ,  G06F40/216 ,  G06F40/35 ,  G06N20/00 ,  H04L51/02

CPC classification number: G06F40/284 ,  G06F18/23213 ,  G06F18/24 ,  G06F40/216 ,  G06F40/35 ,  G06N20/00 ,  H04L51/02

Abstract: Techniques are described to determine whether an input utterance is unrelated to a set of skill bots associated with a master bot. In some embodiments, a system described herein includes a training system and a master bot. The training system trains a classifier of the master bot. The training includes accessing training utterances associated with the skill bots and generating training feature vectors from the training utterances. The training further includes generating multiple set representations of the training feature vectors, where each set representation corresponds to a subset of the training feature vectors, and configuring the classifier with the set representations. The master bot accesses an input utterance and generates an input feature vector. The master bot uses the classifier to compare the input feature vector to the multiple set representations so as to determine whether the input feature falls outside and, thus, cannot be handled by the skill bots.

公开(公告)号：US20210083994A1

公开(公告)日：2021-03-18

申请号：US17017076

申请日：2020-09-10

Applicant: Oracle International Corporation

Inventor： Crystal C. Pan ,  Gautam Singaraju ,  Vishal Vishnoi ,  Srinivasa Phani Kumar Gadde

IPC: H04L12/58 ,  G06K9/62 ,  G06N20/00

Abstract: Techniques are described to determine whether an input utterance is unrelated to a set of skill bots associated with a master bot. In some embodiments, a system described herein includes a training system and a master bot. The training system trains a classifier of the master bot. The training includes accessing training utterances associated with the skill bots and generating training feature vectors from the training utterances. The training further includes generating multiple set representations of the training feature vectors, where each set representation corresponds to a subset of the training feature vectors, and configuring the classifier with the set representations. The master bot accesses an input utterance and generates an input feature vector. The master bot uses the classifier to compare the input feature vector to the multiple set representations so as to determine whether the input feature falls outside and, thus, cannot be handled by the skill bots.

公开(公告)号：US20240289555A1

公开(公告)日：2024-08-29

申请号：US18659606

申请日：2024-05-09

Applicant: Oracle International Corporation

Inventor： Thanh Long Duong ,  Mark Edward Johnson ,  Vishal Vishnoi ,  Crystal C. Pan ,  Vladislav Blinov ,  Cong Duy Vu Hoang ,  Elias Luqman Jalaluddin ,  Duy Vu ,  Balakota Srinivas Vinnakota

IPC: G06F40/30 ,  G06F40/205 ,  G06F40/289 ,  G06N20/00 ,  H04L51/02

CPC classification number: G06F40/30 ,  G06F40/289 ,  G06N20/00 ,  H04L51/02 ,  G06F40/205

Abstract: The present disclosure relates to techniques for identifying out-of-domain utterances. One particular technique includes receiving an utterance and a target domain of a chatbot, generating a sentence embedding for the utterance, obtaining an embedding representation for each cluster of in-domain utterances associated with the target domain, predicting, using a metric learning model, a first probability that the utterance belongs to the target domain based on a similarity or difference between the sentence embedding and each embedding representation for each cluster, predicting, using an outlier detection model, a second probability that the utterance belongs to the target domain based on a determined distance or density deviation between the sentence embedding and embedding representations for neighboring clusters, evaluating the first probability and the second probability to determine a final probability, and classifying the utterance as in-domain or out-of-domain for the chatbot based on the final probability.

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.

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.