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公开(公告)号：US11790181B2
公开(公告)日：2023-10-17
申请号：US16997494
申请日：2020-08-19
发明人： Xiaoxiao Guo , Mo Yu , Yupeng Gao , Chuang Gan , Shiyu Chang , Murray Scott Campbell
IPC分类号： G06F40/35 , G06N3/08 , G06F40/295 , G06F40/253 , G06F40/284
CPC分类号： G06F40/35 , G06F40/253 , G06F40/284 , G06F40/295 , G06N3/08
摘要： A current observation expressed in natural language is received. Entities in the current observation are extracted. A relevant historical observation is retrieved, which has at least one of the entities in common with the current observation. The current observation and the relevant historical observation are combined as observations. The observations and a template list specifying a list of verb phrases to be filled-in with at least some of the entities are input to a neural network, which can output the template list of the verb phrases filled-in with said at least some of the entities. The neural network can include attention mechanism. A reward associated with the neural network's output can be received and fed back to the neural network for retraining the neural network.
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公开(公告)号：US20210117508A1
公开(公告)日：2021-04-22
申请号：US16658120
申请日：2019-10-20
发明人： Shiyu Chang , Mo Yu , Yang Zhang , Tommi S. Jaakkola
摘要： A method and system of training a natural language processing network are provided. A corpus of data is received and one or more input features selected therefrom by a generator network. The one or more selected input features from the generator network are received by a first predictor network and used to predict a first output label. A complement of the selected input features from the generator network are received by a second predictor network and used to predict a second output label.
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公开(公告)号：US20210034965A1
公开(公告)日：2021-02-04
申请号：US16530457
申请日：2019-08-02
发明人： Ming Tan , Dakuo Wang , Mo Yu , Haoyu Wang , Yang Yu , Shiyu Chang , Saloni Potdar
摘要： A computer-implemented method includes using an embedding network to generate prototypical vectors. Each prototypical vector is based on a corresponding label associated with a first domain. The computer-implemented method also includes using the embedding network to generate an in-domain test vector based on at least one data sample from a particular label associated with the first domain and using the embedding network to generate an out-of-domain test vector based on at least one other data sample associated with a different domain. The computer-implemented method also includes comparing the prototypical vectors to the in-domain test vector to generate in-domain comparison values and comparing the prototypical vectors to the out-of-domain test vector to generate out-of-domain comparison values. The computer-implemented method also includes modifying, based on the in-domain comparison values and the out-of-domain comparison values, one or more parameters of the embedding network.
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公开(公告)号：US10459900B2
公开(公告)日：2019-10-29
申请号：US15183742
申请日：2016-06-15
发明人： Ying Chen , Ioana Roxana Stanoi , Su Yan , Mo Yu
摘要： A set of documents is parsed. Members of the set of documents include a set of text elements and a set of visual elements. A text content stream based on the set of text elements and a visual content stream based on the set of visual elements are produced. For respective documents, a set of respective visual element summarizations is built from the visual content stream. Each visual summarization includes a text description of a respective visual element in the respective document. A holistic index is created by indexing the text content from the text content stream and the text descriptions of the visual elements in a single search index. The indexing uses a set of semantic relationships between the text content from the text content stream and the textual descriptions of the visual elements. A user interface allows a user to selectively search text content and visual content.
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公开(公告)号：US11657271B2
公开(公告)日：2023-05-23
申请号：US16658122
申请日：2019-10-20
发明人： Shiyu Chang , Mo Yu , Yang Zhang , Tommi S. Jaakkola
CPC分类号： G06N3/08 , G06N3/0454 , G06K9/6267 , G06N3/0445
摘要： A method and system of determining an output label rationale are provided. A first generator receives a first class of data and selects one or more input features from the first class of data. A first predictor receives the one or more selected input features from the first generator and predicts a first output label. A second generator receives a second class of data and selects one or more input features from the second class of data. A second predictor receives the one or more selected input features from the second generator and predicts a second output label. A discriminator receives the first and second output labels and determines whether the selected one or more input features from the first class of data or the selected features of the one or more input features from the second class of data, more accurately represents the first output label.
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公开(公告)号：US20220335270A1
公开(公告)日：2022-10-20
申请号：US17231289
申请日：2021-04-15
发明人： Tengfei Ma , Manling Li , Mo Yu , Tian GAO , LINGFEI WU
IPC分类号： G06N3/04
摘要： Aspects of the present disclosure relate to knowledge graph compression. An input knowledge graph (KG) can be received. The input KG can be encoded to receive a first set of node embeddings. The input KG can be compressed into an output KG. The output KG can be encoded to receive a second set of node embeddings. A model for KG compression can be trained using optimal transport based on a distance matrix between the first set of node embeddings and the second set of node embeddings.
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公开(公告)号：US11288578B2
公开(公告)日：2022-03-29
申请号：US16597937
申请日：2019-10-10
发明人： Dakuo Wang , Ming Tan , Mo Yu , Haoyu Wang , Yupeng Gao , Chuang Gan
摘要： A computer system identifies threads in a communication session. A feature vector is generated for a message in a communication session, wherein the feature vector includes elements for features and contextual information of the message. The message feature vector and feature vectors for a plurality of threads are processed using machine learning models each associated with a corresponding thread to determine a set of probability values for classifying the message into at least one thread, wherein the threads include one or more pre-existing threads and a new thread. A classification of the message into at least one of the threads is indicated based on the set of probability values. Classification of one or more prior messages is adjusted based on the message's classification. Embodiments of the present invention further include a method and program product for identifying threads in a communication session in substantially the same manner described above.
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公开(公告)号：US11093469B2
公开(公告)日：2021-08-17
申请号：US16536968
申请日：2019-08-09
发明人： Ying Chen , Ioana Roxana Stanoi , Su Yan , Mo Yu
摘要： A set of documents is parsed. Members of the set of documents include a set of text elements and a set of visual elements. A text content stream based on the set of text elements and a visual content stream based on the set of visual elements are produced. For respective documents, a set of respective visual element summarizations is built from the visual content stream. Each visual summarization includes a textual description of a respective visual element in the respective document. A holistic index is created by indexing the text content from the text content stream and the text descriptions of the visual elements for each document in a single search index. The indexing uses a set of semantic relationships between the text content from the text content stream and the textual descriptions of the visual elements. A user interface allows a user to selectively search text content and visual content.
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公开(公告)号：US11989237B2
公开(公告)日：2024-05-21
申请号：US16551021
申请日：2019-08-26
发明人： Dakuo Wang , Ming Tan , Chuang Gan , Haoyu Wang , Mo Yu
IPC分类号： G06F16/9032 , G06N5/04
CPC分类号： G06F16/90332 , G06N5/04
摘要： An artificial intelligence (AI) interaction method, system, and computer program product include selecting an artificial intelligence model to respond to a query to generating a response to the query using the selected artificial intelligence model, and receiving the response to the query from the selected artificial intelligence model.
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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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