With the development of information construction,China's public safety accumulated massive data,how to analyze these data effectively worthy of study.With the continuous improvement of the data management system,intelligence analysis algorithms more and more be valued by the decision makers.But the existing intelligence analysis system does not support the algorithm crowdsourcing and algorithm configuring.Then,this article has done the following work:Firstly,the crowdsourcing framework of the algorithm for public safety intelligence analysis is put forward.This paper constructs the domain ontology model of public safety intelligence analysis based on the eABC theory and the "object-behavior-event-block" multi-layer heterogeneous complex network,and establishes the intelligence analysis algorithm system.Then,the crowdsourcing framework of the algorithm is proposed.Secondly,the algorithm configuring model is designed.Using the ontology mapping method,the data set and the ontology model are mapped to establish the correlation relation between the data set and the relationship between the data items.Then,the algorithm configuring model being designed,including input parameters configuring and input data configuring.Finally,the design and implementation of the algorithm crowdsourcing platform are completed.The platform is described from the framework digram,the business flow diagram and the data flow diagram,and the platform details are designed from the perspective of the software architecture.Realized and demonstrated the system,verified the platform design.In this paper,the algorithm crowdsourcing framework of the public safety intelligence analysis of multi-layer heterogeneous complex network,the configurable algorithm model,and platform-based instantiating design are put forward.Platforms based on this framework have extensive compatibility with data sources and new algorithms,and make the implementation of intelligence analytics flexible. |