Dynamic event-based network semantic model rebuilding system and method

A semantic model and reconstruction system technology, applied in special data processing applications, instruments, electrical digital data processing, etc., can solve the problems of not supporting the flexibility of application and innovation based on digital information models, and meet the needs of data analysis, Apply flexible effects to upper layers

Active Publication Date: 2018-11-02
SIEMENS CHINA
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

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Benefits of technology

This patented technology allows for creating an adaptive representation or structure that reflects how well certain parts of the world are connected together by default (dynamic) systems such as time stamps or movement). It also uses advanced techniques like machine learning methods to analyze past behavior patterns from real life sources into knowledge about future ones. Overall this helps improve understanding complex networks through their temporal dynamics and content analytical capabilities.

Problems solved by technology

This patented describes how domains in physics can gather relevant data about things like water distribution systems without being restricted due to changes made during their operation. To address this problem, researchers have developed models called Dynamic Semantic Information Model Layer(SAML). These layers allow users to define customizable rules when analyzing new datasets. They also provide flexibilities over different types of analytical processes, making them ideal tools for studying complex scenarios involving multiple sources of data.

Method used

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  • Dynamic event-based network semantic model rebuilding system and method
  • Dynamic event-based network semantic model rebuilding system and method
  • Dynamic event-based network semantic model rebuilding system and method

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Embodiment Construction

[0040] The technical solutions of the embodiments of the present disclosure will be clearly and completely described below in conjunction with the accompanying drawings of the embodiments of the present disclosure. Apparently, the described embodiments are only some of the embodiments of the present disclosure, not all of them.

[0041] figure 1 It is a block diagram showing a network semantic model reconstruction system based on dynamic events according to an embodiment of the present invention. The network semantic model reconstruction system 100 based on dynamic events according to the present invention includes a system data receiving module 101 , an event generation module 102 , a relationship correlation module 103 and a network semantic relationship reconstruction module 104 . The system data receiving module 101 receives system data. The event generating module 102 generates system events based on the system data received by the system data receiving module 101 . The r

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Abstract

The invention relates to a dynamic event-based network semantic model rebuilding system and method. The dynamic event-based network semantic model rebuilding system comprises a system data receiving module used for receiving system data, an event generating module used for generating a system event based on the system data, a relation association module used for associating a network semantic relation of a network semantic information model with the system event, and a network semantic relation reconstitution module used for reconstructing the network semantic relation by utilizing a domain data analysis algorithm through analyzing the network semantic information model associated with the system event to form a new dynamic network semantic model. The new dynamic semantic model is overlapped with an existing network information model, and is changed when the system event is changed, so that context information of a virtual network is more flexible for upper application of data analysis, and data analysis needs under different application scenes can be met.

Description

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Claims

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Application Information

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Owner SIEMENS CHINA
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