Invention Grant
- Patent Title: Learnable contextual network
- Patent Title (中): 可学习的上下文网络
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Application No.: US13428850Application Date: 2012-03-23
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Publication No.: US09015086B2Publication Date: 2015-04-21
- Inventor: Robert Heidasch
- Applicant: Robert Heidasch
- Applicant Address: DE Walldorf
- Assignee: SAP SE
- Current Assignee: SAP SE
- Current Assignee Address: DE Walldorf
- Agency: Schwegman Lundberg & Woessner, P.A.
- Main IPC: G06N7/00
- IPC: G06N7/00 ; G06N3/04

Abstract:
A method and apparatus for detection of relationships between objects in a meta-model semantic network is described. Semantic objects and semantic relations of a meta-model of business objects are generated from a meta-model semantic network. The semantic relations are based on connections between the semantic objects. A neural network is formed based on usage of the semantic objects and the semantic relations. The neural network is integrated with the semantic objects and the semantic relations to generate a contextual network. A statistical analysis of the connections between the semantic objects in the contextual network is performed to identify stronger semantic relations. The identified stronger semantic relations are used to update the neural network. The updated neural network is integrated into the contextual network.
Public/Granted literature
- US20130254144A1 LEARNABLE CONTEXTUAL NETWORK Public/Granted day:2013-09-26
Information query
IPC分类:
G | 物理 |
G06 | 计算;推算或计数 |
G06N | 基于特定计算模型的计算机系统 |
G06N7/00 | 基于特定数学模式的计算机系统 |