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1.发明授权公开(公告)号：US11551135B2
公开(公告)日：2023-01-10
申请号：US16147270
申请日：2018-09-28
Applicant: Oracle International Corporation
Inventor： Gautam Singaraju , Jiarui Ding , Sangameswaran Viswanathan
IPC: G06F7/00 , G06N20/00 , G06F16/28 , G06F16/22 , H04L51/04 , G06N5/00 , H04L51/02 , G06F16/9032 , G06N20/10 , G06F40/35 , G06N3/08 , G10L15/06 , G10L15/18 , G06F16/31 , G06F16/35 , G06F16/33 , G06K9/62 , G10L15/16
Abstract: Techniques disclosed herein relate to generating a hierarchical classification model that includes a plurality of classification models. The hierarchical classification model is configured to classify an input into a class in a plurality of classes and includes a tree structure. The tree structure includes leaf nodes and non-leaf nodes. Each non-leaf node has two child nodes associated with two respective sets of classes in the plurality of classes, where a difference between numbers of classes in the two sets of classes is zero or one. Each leaf node is associated with at least two but fewer than a first threshold number of classes. Each of the leaf nodes and non-leaf nodes is associated with a classification model in the plurality of classification models of the hierarchical classification model. The classification model associated with each respective node in the tree structure can be trained independently.
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公开(公告)号：US20210012245A1
公开(公告)日：2021-01-14
申请号：US17038571
申请日：2020-09-30
Applicant: Oracle International Corporation
Inventor： Gautam Singaraju , Jiarui Ding , Vishal Vishnoi , Mark Joseph Sugg , Edward E. Wong
IPC: G06N20/00 , G06F16/28 , G06F16/22 , H04L12/58 , G06N5/00 , G06F16/9032 , G06N20/10 , G06F40/35 , G06N3/08 , G10L15/06 , G10L15/18 , G06F16/31 , G06F16/35 , G06F16/33 , G06K9/62
Abstract: Techniques disclosed herein relate to improving quality of classification models for differentiating different user intents by improving the quality of training samples used to train the classification models. Pairs of user intents that are difficult to differentiate by classification models trained using the given training samples are identified based upon distinguishability scores (e.g., F-scores). For each of the identified pairs of intents, pairs of training samples each including a training sample associated with a first intent and a training sample associated with a second intent in the pair of intents are ranked based upon a similarity score between the two training samples in each pair of training samples. The identified pairs of intents and the pairs of training samples having the highest similarity scores may be presented to users through a user interface, along with user-selectable options or suggestions for improving the training samples.
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公开(公告)号：US10824962B2
公开(公告)日：2020-11-03
申请号：US16147266
申请日：2018-09-28
Applicant: Oracle International Corporation
Inventor： Gautam Singaraju , Jiarui Ding , Vishal Vishnoi , Mark Joseph Sugg , Edward E. Wong
IPC: G06N20/10 , G06N20/00 , G06F16/28 , G06F16/22 , H04L12/58 , G06N5/00 , G06F16/9032 , G06F40/35 , G06N3/08 , G10L15/06 , G10L15/18 , G06F16/31 , G06F16/35 , G06F16/33 , G06K9/62 , G10L15/16
Abstract: Techniques for improving quality of classification models for differentiating different user intents by improving the quality of training samples used to train the classification models are described. Pairs of user intents that are difficult to differentiate by classification models trained using the given training samples are identified based upon distinguishability scores (e.g., F-scores). For each of the identified pairs of intents, pairs of training samples each including a training sample associated with a first intent and a training sample associated with a second intent in the pair of intents are ranked based upon a similarity score between the two training samples in each pair of training samples. The identified pairs of intents and the pairs of training samples having the highest similarity scores may be presented to users through a user interface, along with user-selectable options or suggestions for improving the training samples.
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Patent Agency Ranking
公开(公告)号：US11416777B2
公开(公告)日：2022-08-16
申请号：US17038571
申请日：2020-09-30
Applicant: Oracle International Corporation
Inventor： Gautam Singaraju , Jiarui Ding , Vishal Vishnoi , Mark Joseph Sugg , Edward E. Wong
IPC: G06F16/28 , G06N20/00 , G06F16/22 , H04L51/04 , G06N5/00 , H04L51/02 , G06F16/9032 , G06N20/10 , G06F40/35 , G06N3/08 , G10L15/06 , G10L15/18 , G06F16/31 , G06F16/35 , G06F16/33 , G06K9/62 , G10L15/16
Abstract: Techniques herein relate to improving quality of classification models for differentiating different user intents by improving the quality of training samples used to train the classification models. Pairs of user intents that are difficult to differentiate by classification models trained using the given training samples are identified based upon distinguishability scores (e.g., F-scores). For each of the identified pairs of intents, pairs of training samples each including a training sample associated with a first intent and a training sample associated with a second intent in the pair of intents are ranked based upon a similarity score between the two training samples in each pair of training samples. A particular pair of training samples with a highest similarity score is selected and provided as output with a suggestion for modifying the particular pair of training samples.
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5.发明申请公开(公告)号：US20190102701A1
公开(公告)日：2019-04-04
申请号：US16147270
申请日：2018-09-28
Applicant: Oracle International Corporation
Inventor： Gautam Singaraju , Jiarui Ding , Sangameswaran Viswanathan
Abstract: Techniques disclosed herein relate to generating a hierarchical classification model that includes a plurality of classification models. The hierarchical classification model is configured to classify an input into a class in a plurality of classes and includes a tree structure. The tree structure includes leaf nodes and non-leaf nodes. Each non-leaf node has two child nodes associated with two respective sets of classes in the plurality of classes, where a difference between numbers of classes in the two sets of classes is zero or one. Each leaf node is associated with at least two but fewer than a first threshold number of classes. Each of the leaf nodes and non-leaf nodes is associated with a classification model in the plurality of classification models of the hierarchical classification model. The classification model associated with each respective node in the tree structure can be trained independently.
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6.发明申请公开(公告)号：US20190102345A1
公开(公告)日：2019-04-04
申请号：US16147273
申请日：2018-09-28
Applicant: Oracle International Corporation
Inventor： Gautam Singaraju , Jiarui Ding , Sangameswaran Viswanathan
Abstract: Techniques disclosed herein relate to querying a hierarchical classification model that includes a plurality of classification models. The hierarchical classification model is configured to classify an input into a class in a plurality of classes and includes a tree structure. The tree structure includes leaf nodes and non-leaf nodes. Each non-leaf node has two child nodes associated with two respective sets of classes in the plurality of classes, where a difference between numbers of classes in the two sets of classes is zero or one. Each leaf node is associated with at least two but fewer than a first threshold number of classes. Each of the leaf nodes and non-leaf nodes is associated with a classification model in the plurality of classification models of the hierarchical classification model. The classification model associated with each respective node in the tree structure can be trained independently.
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公开(公告)号：US10733538B2
公开(公告)日：2020-08-04
申请号：US16147273
申请日：2018-09-28
Applicant: Oracle International Corporation
Inventor： Gautam Singaraju , Jiarui Ding , Sangameswaran Viswanathan
IPC: G06F16/28 , G06N20/00 , G06F16/22 , H04L12/58 , G06N5/00 , G06F16/9032 , G06N20/10 , G06F40/35 , G06N3/08 , G10L15/06 , G10L15/18 , G06F16/31 , G06F16/35 , G06F16/33 , G06K9/62 , G10L15/16
Abstract: Techniques disclosed herein relate to querying a hierarchical classification model that includes a plurality of classification models. The hierarchical classification model is configured to classify an input into a class in a plurality of classes and includes a tree structure. The tree structure includes leaf nodes and non-leaf nodes. Each non-leaf node has two child nodes associated with two respective sets of classes in the plurality of classes, where a difference between numbers of classes in the two sets of classes is zero or one. Each leaf node is associated with at least two but fewer than a first threshold number of classes. Each of the leaf nodes and non-leaf nodes is associated with a classification model in the plurality of classification models of the hierarchical classification model. The classification model associated with each respective node in the tree structure can be trained independently.
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公开(公告)号：US20190103095A1
公开(公告)日：2019-04-04
申请号：US16147266
申请日：2018-09-28
Applicant: Oracle International Corporation
Inventor： Gautam Singaraju , Jiarui Ding , Vishal Vishnoi , Mark Joseph Sugg , Edward E. Wong
Abstract: Techniques disclosed herein relate to improving quality of classification models for differentiating different user intents by improving the quality of training samples used to train the classification models. Pairs of user intents that are difficult to differentiate by classification models trained using the given training samples are identified based upon distinguishability scores (e.g., F-scores). For each of the identified pairs of intents, pairs of training samples each including a training sample associated with a first intent and a training sample associated with a second intent in the pair of intents are ranked based upon a similarity score between the two training samples in each pair of training samples. The identified pairs of intents and the pairs of training samples having the highest similarity scores may be presented to users through a user interface, along with user-selectable options or suggestions for improving the training samples.
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