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公开(公告)号：US20210240675A1
公开(公告)日：2021-08-05
申请号：US16780481
申请日：2020-02-03
Applicant: SAP SE
Inventor： Jan Portisch , Bjoern Pantel , Benjamin Merkle , Stephan Schub , Sandra Bracholdt , Roland Kolata , Michael Hladik , Christoph Meinel
Abstract: Techniques and solutions are described for converting data models between formats, such as between a conceptual data model and a physical data model for a database system, or between a conceptual data model and artefacts to be implemented in the database system. The conceptual data model is annotated with annotations that allow the physical data model or database artefacts to be automatically generated from the conceptual data model. The annotations can reflect relationships between entity types in the physical data model, such as inheritance relationships, header/item relationships, or one-to-one cardinality relationships. Annotations can also indicate attributes that should be added to entity types in the conceptual data model, such as attributes for versioning or data governance, that may not be used in the conceptual data model. Annotations can be used to determine how entity types in the conceptual data model will be denormalized in the physical data model.
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Patent Agency Ranking
公开(公告)号：US09223777B2
公开(公告)日：2015-12-29
申请号：US14536040
申请日：2014-11-07
Applicant: SAP SE , intelligent views gmbh
Inventor： Robert Heidasch , Stefan Scheidl , Klaus Reichenberger , Steffen Moldaner , Archim Heimann , Stephan Brand , Nico Licht , Michael Neumann , Christoph Meinel
CPC classification number: G06F17/2785 , G06F17/30321 , G06F17/3053 , G06F17/30864 , G06N99/005
Abstract: A method, machine readable storage medium, and system for providing a self learning semantic search engine. A semantic network may be set up with initial configuration. A search engine coupled to the semantic network may build indexes and semantic indexes. A user request for business data may be received. The search engine may be accessed via a semantic dispatcher. And based on the access, search engine may update the indexes and semantic indexes.
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公开(公告)号：US11762820B2
公开(公告)日：2023-09-19
申请号：US17887267
申请日：2022-08-12
Applicant: SAP SE
Inventor： Jan Portisch , Bjoern Pantel , Benjamin Merkle , Stephan Schub , Sandra Bracholdt , Roland Kolata , Michael Hladik , Christoph Meinel
CPC classification number: G06F16/212 , G06F16/213 , G06F16/2282 , G06F16/288
Abstract: Techniques and solutions are described for converting data models between formats, such as between a conceptual data model and a physical data model for a database system, or between a conceptual data model and artefacts to be implemented in the database system. The conceptual data model is annotated with annotations that allow the physical data model or database artefacts to be automatically generated from the conceptual data model. The annotations can reflect relationships between entity types in the physical data model, such as inheritance relationships, header/item relationships, or one-to-one cardinality relationships. Annotations can also indicate attributes that should be added to entity types in the conceptual data model, such as attributes for versioning or data governance, that may not be used in the conceptual data model. Annotations can be used to determine how entity types in the conceptual data model will be denormalized in the physical data model.
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公开(公告)号：US20220391363A1
公开(公告)日：2022-12-08
申请号：US17887267
申请日：2022-08-12
Applicant: SAP SE
Inventor： Jan Portisch , Bjoern Pantel , Benjamin Merkle , Stephan Schub , Sandra Bracholdt , Roland Kolata , Michael Hladik , Christoph Meinel
Abstract: Techniques and solutions are described for converting data models between formats, such as between a conceptual data model and a physical data model for a database system, or between a conceptual data model and artefacts to be implemented in the database system. The conceptual data model is annotated with annotations that allow the physical data model or database artefacts to be automatically generated from the conceptual data model. The annotations can reflect relationships between entity types in the physical data model, such as inheritance relationships, header/item relationships, or one-to-one cardinality relationships. Annotations can also indicate attributes that should be added to entity types in the conceptual data model, such as attributes for versioning or data governance, that may not be used in the conceptual data model. Annotations can be used to determine how entity types in the conceptual data model will be denormalized in the physical data model.
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公开(公告)号：US11442907B2
公开(公告)日：2022-09-13
申请号：US16780481
申请日：2020-02-03
Applicant: SAP SE
Inventor： Jan Portisch , Bjoern Pantel , Benjamin Merkle , Stephan Schub , Sandra Bracholdt , Roland Kolata , Michael Hladik , Christoph Meinel
Abstract: Techniques and solutions are described for converting data models between formats, such as between a conceptual data model and a physical data model for a database system, or between a conceptual data model and artefacts to be implemented in the database system. The conceptual data model is annotated with annotations that allow the physical data model or database artefacts to be automatically generated from the conceptual data model. The annotations can reflect relationships between entity types in the physical data model, such as inheritance relationships, header/item relationships, or one-to-one cardinality relationships. Annotations can also indicate attributes that should be added to entity types in the conceptual data model, such as attributes for versioning or data governance, that may not be used in the conceptual data model. Annotations can be used to determine how entity types in the conceptual data model will be denormalized in the physical data model.
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公开(公告)号：US20150058315A1
公开(公告)日：2015-02-26
申请号：US14536040
申请日：2014-11-07
Applicant: SAP SE , intelligent views gmbh
Inventor： Robert Heidasch , Stefan Scheidl , Klaus Reichenberger , Steffen Moldaner , Archim Heimann , Stephan Brand , Nico Licht , Michael Neumann , Christoph Meinel
CPC classification number: G06F17/2785 , G06F17/30321 , G06F17/3053 , G06F17/30864 , G06N99/005
Abstract: A method, machine readable storage medium, and system for providing a self learning semantic search engine. A semantic network may be set up with initial configuration. A search engine coupled to the semantic network may build indexes and semantic indexes. A user request for business data may be received. The search engine may be accessed via a semantic dispatcher. And based on the access, search engine may update the indexes and semantic indexes.
Abstract translation: 一种用于提供自学习语义搜索引擎的方法，机器可读存储介质和系统。 可以使用初始配置来建立语义网络。 耦合到语义网络的搜索引擎可以构建索引和语义索引。 可以接收用户对业务数据的请求。 可以通过语义调度器来访问搜索引擎。 基于访问，搜索引擎可以更新索引和语义索引。
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