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公开(公告)号：US20230394329A1
公开(公告)日：2023-12-07
申请号：US18026533
申请日：2021-09-01
IPC分类号： G06N5/022
CPC分类号： G06N5/022
摘要： A classification model is trained with elements from several data sources, with the elements including sensor data mounted in an industrial plant, and with the labels indicating a semantic type for each of the elements. The classification model is retrained with an adaptive learning algorithm implementing active learning and/or incremental learning, until the classification model is capable of mapping each element of the data sources to one of the semantic types. The method and system provide a semantic mapping for sensor data. The automated or semi-automated creation of the semantic mapping loosens the coupling between a domain expert and data scientist, serves as a bridge and reduces workload, speeding up data modeling and data integration steps. It provides inexperienced users with access to domain expertise. Re-use of data models is facilitated, which simplifies further integration and exchange activities. The adaptive learning algorithm provides an incremental enhancement of the classification model.
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2.发明申请公开(公告)号：US20220253877A1
公开(公告)日：2022-08-11
申请号：US17628214
申请日：2019-07-19
IPC分类号： G06Q30/02
摘要： The invention is directed to a computer-implemented method for determining at least one completed item of at least one product solution, comprising the steps of: a. Providing at least one input data set with at least one partial item of the at least one product solution; wherein b. the at least one partial item comprises at least one initial feature; c. Complementing the at least one partial item of the at least one product solution with at least one additional alternative feature using a trained machine learning model on the basis of at least one partial item of the at least one product solution to determine a plurality of alternative complete items of the at least one product solution; and d. Determining at least one evaluated complete item of the plurality of alternative items of the at least one product solution as output data set using a market impact evaluation. Further, the invention relates to a corresponding computer program product and system.
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公开(公告)号：US12130843B2
公开(公告)日：2024-10-29
申请号：US18263852
申请日：2022-01-27
发明人： Swathi Shyam Sunder , Tobias Aigner
CPC分类号： G06F16/285 , G06F16/211
摘要： Various embodiments of the teachings herein include a computer-aided method for transforming data in a relational database, containing sensor measurements, into RDF data blocks of a graph database. The method may include: providing a R2RML mapping file; breaking down and converting the data using the mapping file and a first mapping parser; generating a generation of RDF data blocks; and storing the generation as a database. After the data have been broken down and converted, checking a quality of the obtained R2RML mapping and creating a second R2RML mapping file, on the basis of which the relational data are broken down and converted into RDF data blocks. The second R2RML mapping, during the preparation of the relational data into RDF data blocks, automatically stops the processing of relational data that are not to be resolved and thus optimizes the energy efficiency of the preparation.
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公开(公告)号：US11243526B2
公开(公告)日：2022-02-08
申请号：US17267932
申请日：2019-08-12
发明人： Christoph Bergs , Marcel Hildebrandt , Mohamed Khalil , Serghei Mogoreanu , Swathi Shyam Sunder
摘要： A plurality of basic simulations independent of one another are carried out, which determine respective remaining service life predictions for the machine. The remaining service life predictions and characteristic data are fed to a neural network, which outputs weights for the remaining service life predictions. A final prediction is calculated from the remaining service life predictions by weighting the remaining service life predictions relative to one another. A hybrid model is produced, which results from the combination of the basic simulations with the neural network. The remaining service life can be predicted not only for a small number of machines for which a specific simulation model has been manually created. The hybrid model enables condition monitoring for any further types and configurations of machines that merely belong to the same machine class. The basic simulations can therefore also be applied to previously unknown machines.
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5.发明申请公开(公告)号：US20220284286A1
公开(公告)日：2022-09-08
申请号：US17637234
申请日：2020-08-18
IPC分类号： G06N3/08 , G06N3/04 , G06F3/0482
摘要： Provided is a recommendation engine to provide automatically recommendations for the completion of an engineering project, the recommendation engine including: a first artificial intelligence, AI, module adapted to provide latent representations of a sequence of selected items; and a second artificial intelligence, AI, module adapted to process the latent representations of the sequence of selected items provided by the first artificial intelligence, AI, module to generate at least one sequence of complementary items required to complement the sequence of selected items to provide a complete sequence of items output via an interface as a recommendation to complete the engineering project.
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公开(公告)号：US20240338379A1
公开(公告)日：2024-10-10
申请号：US18294716
申请日：2022-08-02
发明人： Tobias Aigner , Swathi Shyam Sunder
IPC分类号： G06F16/25
CPC分类号： G06F16/258
摘要： Various embodiments of the teachings herein include a method for selecting automatically a suitable R2RML engine component. An example includes: reading input from a database or an input component; processing the input with a data processing component; selecting a suitable R2RML engine component including the data processing component using a R2RML engine selection component “RESC”; selecting the most suitable R2RML engine component or one out of the number of equally suitable R2RML engine components; using the selected R2RML engine component to process the input data; executing the selected R2RML engine component to generate results; transferring the results to an output component; and writing the results transmitted from the Data Processing component through the output component. The R2RML engine selection component “RESC” provides either: an identification of a most suitable R2RML engine component, and/or a ranking list of all suitable R2RML engine components suitable for mapping the given input.
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公开(公告)号：US20240119067A1
公开(公告)日：2024-04-11
申请号：US18263852
申请日：2022-01-27
发明人： Swathi Shyam Sunder , Tobias Aigner
CPC分类号： G06F16/285 , G06F16/211
摘要： Various embodiments of the teachings herein include a computer-aided method for transforming data in a relational database, containing sensor measurements, into RDF data blocks of a graph database. The method may include: providing a R2RML mapping file; breaking down and converting the data using the mapping file and a first mapping parser; generating a generation of RDF data blocks; and storing the generation as a database. After the data have been broken down and converted, checking a quality of the obtained R2RML mapping and creating a second R2RML mapping file, on the basis of which the relational data are broken down and converted into RDF data blocks. The second R2RML mapping, during the preparation of the relational data into RDF data blocks, automatically stops the processing of relational data that are not to be resolved and thus optimizes the energy efficiency of the preparation.
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公开(公告)号：US20230418802A1
公开(公告)日：2023-12-28
申请号：US18338302
申请日：2023-06-20
CPC分类号： G06F16/2282 , G06F16/211
摘要： A solution for automated column type annotation maps each column contained in a table to a column annotation class. A pre-processor transforms the table into a numerical tensor representation by outputting a sequence of cell tokens for each cell in the table. A table encoder encodes the sequences of cell tokens and a column annotation label for each column into body cell embeddings. A body pooling component processes the body cell embeddings to provide column representations. A classifier classifies the column representations to provide for each column, confidence scores for each column annotation class. The method concludes with comparing the highest confidence score for each column with a threshold, and, if the highest confidence score for each column is above the threshold, annotating each column with the respective column annotation class.
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公开(公告)号：US11741161B2
公开(公告)日：2023-08-29
申请号：US17308377
申请日：2021-05-05
IPC分类号： G06F16/90 , G06F16/9032 , G06F16/901 , G06F16/953 , G06F11/34 , G06F16/9035 , G06F16/20 , G06F11/30
CPC分类号： G06F16/90324 , G06F11/3409 , G06F16/9027 , G06F16/9035 , G06F16/953
摘要： The disclosed relates to a system for generating a refined query, whereby the system comprises or is coupled with a search engine for searching through a tree of query modification operations, whereby the root node of said tree is an empty node which represents a given initial query, and comprises at least one processor which is configured to perform the following steps:
a) defining a set of query modification operators which can be inserted into said tree;
b) receiving a second set of reference query results;
c) receiving a first set of current query results from a currently given query comprising one or more triple patterns;
d) contrasting the first set of query results with the second set of query results by assessing the differences between the two query results;
e) running the search engine which is configured to perform the following steps:
f) selecting a node of said tree by a computed score derived from the assessed result;
g) selecting any query modification operator of the defined set of query modification operators;
h) if the selected query modification operator does not correspond to any of the triple patterns of the query represented by the selected node, then continue step f);
i) otherwise identifying at least one triple pattern of the query which the selected query modification operator corresponds to;
j) generating a refined query by applying the selected query modification operator to the identified triple pattern.-
公开(公告)号：US20220358166A1
公开(公告)日：2022-11-10
申请号：US17308377
申请日：2021-05-05
IPC分类号： G06F16/9032 , G06F16/901 , G06F16/9035 , G06F16/953 , G06F11/34 , G06N20/00
摘要： The disclosed relates to a system for generating a refined query, whereby the system comprises or is coupled with a search engine for searching through a tree of query modification operations, whereby the root node of said tree is an empty node which represents a given initial query, and comprises at least one processor which is configured to perform the following steps:
a) defining a set of query modification operators which can be inserted into said tree; b) receiving a second set of reference query results; c) receiving a first set of current query results from a currently given query comprising one or more triple patterns; d) contrasting the first set of query results with the second set of query results by assessing the differences between the two query results; e) running the search engine which is configured to perform the following steps: f) selecting a node of said tree by a computed score derived from the assessed result; g) selecting any query modification operator of the defined set of query modification operators; h) if the selected query modification operator does not correspond to any of the triple patterns of the query represented by the selected node, then continue step f); i) otherwise identifying at least one triple pattern of the query which the selected query modification operator corresponds to; j) generating a refined query by applying the selected query modification operator to the identified triple pattern.
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