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1.发明申请公开(公告)号：US20220121819A1
公开(公告)日：2022-04-21
申请号：US17506475
申请日：2021-10-20
Applicant: DASSAULT SYSTEMES
Inventor： Xavier GREHANT , Benoit DUVAL , Samu TAMMINEN
IPC: G06F40/279 , G06F40/166
Abstract: A computer implemented method for comparing unsupervised embedding methods for a similarity based industrial component model requesting system including obtaining a text corpus relating to industrial component models and a list of testing words, modifying by altering some of the occurrences of each testing word, the modified text corpus containing, for each testing word, occurrences of a first version of each testing word, and occurrences of a second version of each testing word, running an unsupervised embedding method on the modified text corpus and obtaining vector representations, determining a scoring value, by comparing, for at least some of the testing words, the vector representations of the first version of these testing words, and the vector representations the second version of these testing words, running the obtaining, modifying with the text corpus and the list of testing words with another unsupervised embedding method and returning the respective scoring values.
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公开(公告)号：US20170193049A1
公开(公告)日：2017-07-06
申请号：US15395229
申请日：2016-12-30
Applicant: DASSAULT SYSTEMES
Inventor： Xavier GREHANT
IPC: G06F17/30
CPC classification number: G06F16/24553 , G06F16/22 , G06F16/2272 , G06F16/35 , G06N20/00
Abstract: The invention notably relates to a computer-implemented method for retrieving model outcomes in the course of an event. The method comprises providing variables of a first set of observations of similar events, providing a multiplicity of models, indexing the multiplicity of models with the variables of the first set of observations, querying a model according to one or more variables, and returning, as a result of the query, a model.
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公开(公告)号：US20230393566A1
公开(公告)日：2023-12-07
申请号：US18331052
申请日：2023-06-07
Applicant: DASSAULT SYSTEMES
Inventor： Xavier GREHANT , Arnaud DALIE
IPC: G05B19/418 , G06T7/00
CPC classification number: G05B19/41875 , G06T7/001
Abstract: A computer-implemented method for inferring an emerging problem in product manufacturing. The method comprises obtaining a time-ordered set comprising one or more snapshots of a product and one or more similarity thresholds. The method also comprises obtaining at least one recent snapshot, the at least one recent snapshot being time-ordered after at least one snapshot of the time-ordered set. The method also comprises retrieving a subset of one or more snapshots from the time-ordered set, the one or more snapshots being time-ordered before the at least one recent snapshot and satisfying, with respect to the at least one recent snapshot, a similarity above at least one of the one or more similarity thresholds. The method also comprises determining a trend from the retrieved subset and a baseline, the trend being a time distribution of the snapshots of the retrieved subset with respect to the baseline.
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Patent Agency Ranking
公开(公告)号：US20190197424A1
公开(公告)日：2019-06-27
申请号：US16232650
申请日：2018-12-26
Applicant: Dassault Systemes
Inventor： Xavier GREHANT
CPC classification number: G06N7/005 , G06F9/542 , G06F17/18 , G06F17/50 , G06K9/6215 , G06K9/6232 , G06N20/00
Abstract: The disclosure notably relates to a computer-implemented method for predicting new occurrences of an event of a physical system. The method comprises providing a first set of past events of the physical system, each past event comprising several attributes, providing a signature for each past event of the first set, providing a new event comprising several attributes, computing a signature of the new event, computing a similarity measure between the signature of the new event and each signature of each past event of the first set, determining the past events closest to the new event according to the similarity measures thereby forming a second set of past events, computing a score of relevance for each attribute of the second set, providing a set of attributes by selecting the attributes having the greater scores of relevance.
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公开(公告)号：US20210349429A1
公开(公告)日：2021-11-11
申请号：US17307951
申请日：2021-05-04
Applicant: DASSAULT SYSTEMES
Inventor： Xavier GREHANT
Abstract: A computer implemented method for improving a similarity search of an industrial component model including obtaining a set of industrial component models, each having associated attributes and a similarity embedding, receiving a similarity request using a given industrial component model as an input, the output of said similarity request being a first subset of industrial component models selected from the set of industrial component models based on the comparison between similarity embeddings and the similarity embedding of the input industrial component model, receiving a second subset of industrial component models from said first subset of industrial component models based on an interchangeability criteria of the input industrial component model with any industrial component model of said second subset of industrial component models, associating a similarity attribute to the input industrial component model, and computing a new set of similarity embeddings.
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公开(公告)号：US20170193052A1
公开(公告)日：2017-07-06
申请号：US15395261
申请日：2016-12-30
Applicant: DASSAULT SYSTEMES
Inventor： Xavier GREHANT
CPC classification number: G06F16/24564 , G06F16/35 , G06N20/00
Abstract: The invention notably relates to a computer-implemented method for assessing a potential divergence of an outcome predicted by a machine learning system. The method comprises: training a model on a first set of observations, each observation being associated with a target value; randomly generating a second set of observations; applying the trained model to the second set thereby obtaining a target value associated with each observation of the second set; indexing the first and second sets of observations and their associated target values into an index; receiving a first query allowing a selection of a subset of the first and second sets of observations; generating a second query that comprises the first query and an additional constraint that is to return only observation(s) of the first set; generating a third query that comprises the first query and an additional constraint that is to return only observation(s) of the second set; querying the index using the second and third queries; and returning a response to the second and third queries.
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公开(公告)号：US20170193401A1
公开(公告)日：2017-07-06
申请号：US15395021
申请日：2016-12-30
Applicant: DASSAULT SYSTEMES
Inventor： Xavier GREHANT
CPC classification number: G06N20/00 , G06F16/22 , G06F16/2272 , G06F16/24553 , G06F16/35 , G06N7/005
Abstract: The invention notably relates to a computer-implemented method for selecting an appropriate decision by constraining options assessed with a model. The method comprises selecting a model capable of receiving inputs and providing output in response to an input; training a model with a set of data representing similar events; generating options that represent hypothetical events; computing target values by applying the trained model on the generated options; computing index for indexing the generated options and target values associated with the trained model; querying the said index for obtaining a selection of a set of options, the selection being performed according to a specific constraint; returning, as a result of the query, a subset of the set of the generated options, the subset being ranked according to the target values associated with each option.
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公开(公告)号：US20170140055A1
公开(公告)日：2017-05-18
申请号：US15354870
申请日：2016-11-17
Applicant: DASSAULT SYSTEMES
Inventor： Xavier GREHANT , Morgan Champenois
Abstract: The invention notably relates to a computer-implemented method, performed by a server storing an index of a search engine, for sending, to a client, the URLs of pages of a Web corpus that relates to a theme. The method comprises receiving, from the client, a structured query that corresponds to the theme, the structured query consisting of a disjunction of at least one keyword; determining in the index the group that consists of the URLs of all pages that match the query; and sending to the client the URLs of the group as a stream.Such a method improves the building of a thematic Web corpus.
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