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公开(公告)号：US11928629B2
公开(公告)日：2024-03-12
申请号：US17664719
申请日：2022-05-24
Applicant: INTERNATIONAL BUSINESS MACHINES CORPORATION
Inventor： Siyu Huo , Prabhat Maddikunta Reddy , Vatche Isahagian , Vinod Muthusamy , Prerna Agarwal
IPC: G06Q10/0633 , G06N3/088 , G06Q10/0635
CPC classification number: G06Q10/0633 , G06N3/088 , G06Q10/0635
Abstract: A method, computer system, and a computer program product for anomaly detection is provided. The present invention may include converting business process logs into a graphical data structure. The present invention may include generating an optimized graph encoding for anomaly detection using an unsupervised machine learning model. The present invention may include computing an anomaly score for each activity of the business process log using a process aware metric based on feature representation. The present invention may include labeling each of the one or more data points with a high anomaly score.
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公开(公告)号：US12124811B2
公开(公告)日：2024-10-22
申请号：US17454302
申请日：2021-11-10
Applicant: INTERNATIONAL BUSINESS MACHINES CORPORATION
Inventor： Sebastian Carbajales , Yara Rizk , Vinod Muthusamy , Vatche Isahagian , Kushal Mukherjee , Siyu Huo , Prabhat Maddikunta Reddy , Dario Andres Silva Moran , Allen Vi Cuong Chan
IPC: G06F40/40 , G06F18/21 , G06F18/214 , G06F40/205 , G06N3/02 , G06N3/08
CPC classification number: G06F40/40 , G06F18/214 , G06F18/2178 , G06F40/205 , G06N3/02 , G06N3/08
Abstract: A method, computer system, and a computer program product for generating a conversational bot for an application programming interface (API) is provided. The present invention may include parsing an API schema. The present invention may include generating sentences for the conversational bot from the parsed API schema. The present invention may include constructing the conversational bot by training a deep learning model. The present invention may include receiving a natural language expression from a user. The present invention may include determining whether the natural language expression is enough to activate the bot.
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公开(公告)号：US11853877B2
公开(公告)日：2023-12-26
申请号：US16373149
申请日：2019-04-02
Applicant: International Business Machines Corporation
Inventor： Patrick Watson , Bishwaranjan Bhattacharjee , Siyu Huo , Noel Christopher Codella , Brian Michael Belgodere , Parijat Dube , Michael Robert Glass , John Ronald Kender , Matthew Leon Hill
Abstract: Whether to train a new neural network model can be determined based on similarity estimates between a sample data set and a plurality of source data sets associated with a plurality of prior-trained neural network models. A cluster among the plurality of prior-trained neural network models can be determined. A set of training data based on the cluster can be determined. The new neural network model can be trained based on the set of training data.
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公开(公告)号：US20210098074A1
公开(公告)日：2021-04-01
申请号：US16585679
申请日：2019-09-27
Inventor： Lingfei Wu , Siyu Huo , Tengfei Ma , Pin-Yu Chen , Zhao Qin , Eugene Jungsup Lim , Francisco Javier Martin-Martinez , Hui Sun , Benedetto Marelli , Markus Jochen Buehler
Abstract: A method, computer system, and a computer program product for designing one or more folded structural proteins from at least one raw amino acid sequence is provided. The present invention may include computing one or more character embeddings based on the at least one raw amino acid sequence by utilizing a multi-scale neighborhood-based neural network (MNNN) model. The present invention may then include refining the computed one or more character embeddings with at least one set of sequence neighborhood information. The present invention may further include predicting one or more dihedral angles based on the refined one or more character embeddings.
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公开(公告)号：US20230385732A1
公开(公告)日：2023-11-30
申请号：US17664719
申请日：2022-05-24
Applicant: INTERNATIONAL BUSINESS MACHINES CORPORATION
Inventor： Siyu Huo , Prabhat Maddikunta Reddy , Vatche Isahagian , Vinod Muthusamy , Prerna Agarwal
CPC classification number: G06Q10/0633 , G06Q10/0635 , G06N3/088
Abstract: A method, computer system, and a computer program product for anomaly detection is provided. The present invention may include converting business process logs into a graphical data structure. The present invention may include generating an optimized graph encoding for anomaly detection using an unsupervised machine learning model. The present invention may include computing an anomaly score for each activity of the business process log using a process aware metric based on feature representation. The present invention may include labeling each of the one or more data points with a high anomaly score.
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Patent Agency Ranking
公开(公告)号：US20200320379A1
公开(公告)日：2020-10-08
申请号：US16373149
申请日：2019-04-02
Applicant: International Business Machines Corporation
Inventor： Patrick Watson , Bishwaranjan Bhattacharjee , Siyu Huo , Noel Christopher Codella , Brian Michael Belgodere , Parijat Dube , Michael Robert Glass , John Ronald Kender , Matthew Leon Hill
Abstract: Whether to train a new neural network model can be determined based on similarity estimates between a sample data set and a plurality of source data sets associated with a plurality of prior-trained neural network models. A cluster among the plurality of prior-trained neural network models can be determined. A set of training data based on the cluster can be determined. The new neural network model can be trained based on the set of training data.
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公开(公告)号：US20200082210A1
公开(公告)日：2020-03-12
申请号：US16125153
申请日：2018-09-07
Applicant: International Business Machines Corporation
Inventor： Patrick Watson , Bishwaranjan Bhattacharjee , Siyu Huo , Noel C. Codella , Brian M. Belgodere , Parijat Dube , Michael R. Glass , John R. Kender , Matthew L. Hill
Abstract: A computer-implemented method for data labeling is provided. The computer-implemented method assigns pseudo-labels to unlabeled examples of data using a similarity metric on an embedding space to produce pseudo-labeled examples. A curriculum learning model is trained using the pseudo-labeled examples. The curriculum learning model trained with the pseudo-labeled examples is employed in in a fine-tuning task to enhance classification accuracy of the data.
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公开(公告)号：US20240330601A1
公开(公告)日：2024-10-03
申请号：US18129882
申请日：2023-04-02
Applicant: International Business Machines Corporation
Inventor： Siyu Huo , Vatche Isahagian , Vinod Muthusamy , Praveen Venkateswaran , Kushal Mukherjee , Jayachandu Bandlamudi
IPC: G06F40/40 , G06F40/205 , G06F40/289 , G06F40/30
CPC classification number: G06F40/40 , G06F40/205 , G06F40/289 , G06F40/30
Abstract: An example operation may include one or more of tuning a language model based on dependencies between an original data set and a paraphrase data set of the original data set, parsing and annotating the paraphrase dataset with entity identifiers of predefined entities to generate an annotated paraphrase dataset, additionally tuning the language model based on entity dependencies between the original data set and the paraphrase data set based on the annotated paraphrase dataset, and storing the additionally tuned language model in a storage device.
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公开(公告)号：US20230409898A1
公开(公告)日：2023-12-21
申请号：US17842839
申请日：2022-06-17
Applicant: International Business Machines Corporation , MIT - Massachusetts Institute of Technology
Inventor： Pin-Yu Chen , Siyu Huo , Tengfei Ma , Lingfei Wu , Kai Guo , Federica Rigoldi , Benedetto Marelli , Markus Jochen Buehler
Abstract: A system may include a memory and a processor in communication with the memory. The processor may be configured to perform operations. The operations may include training a neural network and predicting structural feature sets with the neural network. The operations may include producing predicted structures with the neural network using the structural feature sets, converting the predicted structures into predicted graphs with predicted edges, and comparing predicted graphs to training graphs and predicted edges to training edges to obtain a comparison. The operations may include training a model with the comparison, constructing a graph with the neural network using a node feature set, and reducing missing edges in the graph with the model.
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公开(公告)号：US20230153541A1
公开(公告)日：2023-05-18
申请号：US17454302
申请日：2021-11-10
Applicant: INTERNATIONAL BUSINESS MACHINES CORPORATION
Inventor： Sebastian Carbajales , Yara Rizk , Vinod Muthusamy , Vatche Isahagian , Kushal Mukherjee , Siyu Huo , Prabhat Maddikunta Reddy , Dario Andres Silva Moran , Allen Vi Cuong Chan
IPC: G06F40/40 , G06F40/205 , G06K9/62
CPC classification number: G06F40/40 , G06F40/205 , G06K9/6256 , G06K9/6263
Abstract: A method, computer system, and a computer program product for generating a conversational bot for an application programming interface (API)is provided. The present invention may include parsing an API schema. The present invention may include generating sentences for the conversational bot from the parsed API schema. The present invention may include constructing the conversational bot by training a deep learning model. The present invention may include receiving a natural language expression from a user. The present invention may include determining whether the natural language expression is enough to activate the bot.
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