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1.发明公开公开(公告)号：US20240333666A1
公开(公告)日：2024-10-03
申请号：US18192262
申请日：2023-03-29
发明人： Michael Desmond , Zahra Ashktorab , Michelle Brachman , James Johnson , Casey Dugan , Qian Pan
摘要： Provided are techniques for moderating Artificial Intelligence (AI) agent interlocution in group dialog environments. Under control of an interlocution module that has been trained with dialog content and dialog turns, an indication that interlocution is to be determined for a group dialog is received. Under control of the interlocution module, it is determined whether an AI agent is to participate in the group dialog based on a current dialog context and a dialog response. Under control of the interlocution module, in response to determining that the AI agent is to participate in the group dialog, the AI agent is triggered to post the dialog response to the group dialog.
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公开(公告)号：US11824819B2
公开(公告)日：2023-11-21
申请号：US17648941
申请日：2022-01-26
发明人： Qian Pan , James Johnson , Zahra Ashktorab , Dakuo Wang
摘要： A method, a computer program product, and a computer system generate an accurate mental model of an automated agent. The method includes receiving an input from a user device associated with a user during a communication session between the user and the automated agent. The method includes determining a response to the input. The method includes determining a confidence score of the response relative to a confidence threshold. The method includes determining an assertiveness feature associated with the response, the assertiveness feature comprising an expression of the automated agent based on the confidence score. The method includes transmitting the response and the assertiveness feature to the user device, the expression configured to update anthropomorphic characteristics of a graphical representation of the automated agent shown on a graphical user interface of the communication session displayed on a display device of the user device.
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公开(公告)号：US20230316101A1
公开(公告)日：2023-10-05
申请号：US17709520
申请日：2022-03-31
发明人： Qian Pan , James Johnson , Zahra Ashktorab , Casey Dugan
IPC分类号： G06N5/02 , G06F40/284 , G06F40/232 , G06F40/40
CPC分类号： G06N5/022 , G06F40/284 , G06F40/232 , G06F40/40
摘要： Embodiments are provided that related to a computer system, a computer program product, and a computer-implemented method for dynamically managing knowledge graphs and their corresponding datasets. Embodiments include identifying a neologism from a virtual environment, and leveraging a virtual environment exploration to resolve a meaning of the identified neologism. The resolved meaning of the neologism is applied to a dynamic expansion of a dataset and a corresponding knowledge graph.
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公开(公告)号：US20230239258A1
公开(公告)日：2023-07-27
申请号：US17648941
申请日：2022-01-26
发明人： Qian Pan , James Johnson , Zahra Ashktorab , Dakuo Wang
摘要： A method, a computer program product, and a computer system generate an accurate mental model of an automated agent. The method includes receiving an input from a user device associated with a user during a communication session between the user and the automated agent. The method includes determining a response to the input. The method includes determining a confidence score of the response relative to a confidence threshold. The method includes determining an assertiveness feature associated with the response, the assertiveness feature comprising an expression of the automated agent based on the confidence score. The method includes transmitting the response and the assertiveness feature to the user device, the expression configured to update anthropomorphic characteristics of a graphical representation of the automated agent shown on a graphical user interface of the communication session displayed on a display device of the user device.
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公开(公告)号：US20230409553A1
公开(公告)日：2023-12-21
申请号：US17807412
申请日：2022-06-17
发明人： Michelle Brachman , Qian Pan , Narendra Nath Joshi , Aabhas Sharma , Casey Dugan
摘要： A method, computer system, and a computer program product for data labeling is provided. The present invention may include receiving a plurality of labeled data points. The present invention may include identifying one or more of the plurality of labeled data points with conflicting labels. The present invention may include determining that at least one of the one or more identified labeled data points exceeds one or more conflict thresholds. The present invention may include presenting the at least one or more identified labeled data points exceeding one or more conflict thresholds to a user. The present invention may include receiving a conflict resolution from the user for the one or more identified labeled data points exceeding the one or more conflict thresholds.
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公开(公告)号：US11620550B2
公开(公告)日：2023-04-04
申请号：US16989876
申请日：2020-08-10
发明人： Dakuo Wang , Mo Yu , Arunima Chaudhary , Chuang Gan , Qian Pan , Daniel Karl I. Weidele , Abel Valente , Ji Hui Yang
IPC分类号： G06F3/048 , G06N5/04 , G06N20/00 , G06N3/006 , G06F16/2455
摘要： Embodiments relate to a system, program product, and method for leveraging cognitive systems to facilitate the automated data table discovery for automated machine learning, and, more specifically, to leveraging a trained cognitive system to automatically search for additional data in an external data source that may be merged with an initial user-selected data table to generate a more robust machine learning model. Manual efforts to find and validate data appropriate for building and training a particular model for a particular task are significantly reduced. Specifically, a learning-based approach to leverage with machine learning models to automatically discover related datasets and join the datasets for a given initial dataset is disclosed herein. Operations that include dataset selection facilitate continued reinforcement learning of the systems.
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公开(公告)号：US20240282299A1
公开(公告)日：2024-08-22
申请号：US18112858
申请日：2023-02-22
发明人： Michelle Brachman , James Johnson , Qian Pan , Casey Dugan
CPC分类号： G10L15/22 , G10L15/07 , G10L2015/223
摘要： A present invention embodiment analyzes user input via natural language processing. A natural language utterance from a user is analyzed to determine one or more computing tasks. the natural language utterance is analyzed using a knowledge base to identify one or more modifications to the natural language utterance that are based on previous user modifications to a previous user utterance. An indication that the user accepted at least one modification of the one or more modifications is received, wherein the at least one modification modifies the one or more computing tasks. The modified one or more computing tasks are executed.
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公开(公告)号：US20230409838A1
公开(公告)日：2023-12-21
申请号：US17804627
申请日：2022-05-31
发明人： Tathagata Chakraborti , Arunima Chaudhary , Michelle Brachman , Qian Pan , James Johnson , Yara Rizk , Burak Aksar
IPC分类号： G06F40/35
CPC分类号： G06F40/35 , G06F40/205
摘要： A method, computer program, and computer system are provided for explaining generation of a flow from natural language utterances. Data corresponding to a natural language utterance is received. One or more constraints corresponding to a flow to be generated are determined based on the received natural language utterance. A flow is constructed based on the determined constraints. An explanation associated with the constructed flow is provided, and the explanation identifies parameters corresponding to constructing the flow.
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公开(公告)号：US11763084B2
公开(公告)日：2023-09-19
申请号：US16989882
申请日：2020-08-10
发明人： Dakuo Wang , Arunima Chaudhary , Chuang Gan , Mo Yu , Qian Pan , Sijia Liu , Daniel Karl I. Weidele , Abel Valente
IPC分类号： G06F40/289 , G06N20/00 , G06N5/04
CPC分类号： G06F40/289 , G06N5/04 , G06N20/00
摘要： A method comprises receiving a new data set; identifying at least one prior data set of a plurality of prior data sets that matches the new data set; generating a natural language data science problem statement for the new data set based on information associated with the at least prior one data set that matches the new data set; outputting the generated natural language data science problem statement for user verification; and in response to receiving user input verifying the natural language generated data science problem statement, generating one or more AutoAI configuration settings for the new data set based on one or more AutoAI configuration settings associated with the at least one prior data set that matches the new data set.
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