Research And Implementation Of Service Organization Technology Based On Industrial Knowledge Graph

With the continuous expansion of the scale and application fields of the service internet,the scale of service resources on the internet has surged,and the types have become more complex,making it more difficult for users to search for services and increasing the cost of obtaining services.The industrial chain knowledge graph can provide a basic carrier for service organizations to effectively organize services according to relevant industrial fields.This article proposes a service organization method based on industry chain knowledge graph,which effectively organizes services based on the characteristics of industry chain links and services,ultimately forming a global view of industry chain and services.Through this global view,users can search for the services they need through relevant industry fields,which can reduce the cost of searching for services and improve the accuracy of service discovery.How to construct the knowledge graph of the industrial chain and how to map services are two key issues in the service organization technology.The industrial chain knowledge graph is a special kind of knowledge graph,which manages a large amount of industrial chain knowledge in the form of a visual graph,including rich Semantic information and good hierarchical structure.Based on the industry chain knowledge graph,services in related industry fields can be organized and managed.However,there are many problems in the construction process.Firstly,a large amount of structured industry chain data is required,and the lack of relevant field data can lead to low quality of the constructed industry chain knowledge graph.Secondly,the construction process heavily relies on experts in the relevant fields,resulting in high construction costs for a single person.Crowdsourcing technology can effectively gather a large number of crowdsourcing participants to complete a complex task through the collaboration of multiple intelligences,which can effectively collect group intelligence.This article proposes a method for building an industry chain knowledge graph based on crowdsourcing technology.By applying crowdsourcing technology to the process of building an industry chain knowledge graph,it increases the source and quality of data and reduces labor costs.In the process of building a global view of the industrial chain and services,it is necessary to quickly and accurately map the services of related industries.Therefore,calculating the similarity between the industrial chain links and services is a key issue that needs to be addressed.Because the data of industry chain and services contain rich Semantic information and are highly professional,this paper proposes a weighted word2 vec similarity calculation method,which can more accurately reflect the Semantic information of technology service features and industry chain link features,and can also process rare words and words in specific fields.The algorithm also incorporates the calculation of inverse document rate into the similarity algorithm,further improving the discriminative ability of feature words.Finally,this article designed and developed a service organization system based on the industry chain knowledge graph.Provide effective validation for the above research methods and technologies.In the process of building a global view of industry chain knowledge graph and services,this article focuses on solving the following problems: 1.How to use crowdsourcing technology to build a relatively complete industry chain knowledge graph;2.How to accurately map industry chain links and technology services based on the existing industry chain knowledge graph.In response to the above issues,this article studies related technologies such as the construction of industry chain knowledge graph,industry chain links,and service mapping.The main work is as follows:(1)This article proposes a crowdsourcing based method for constructing an industrial chain knowledge graph,which mainly includes three parts: obtaining industrial chain knowledge subgraphs,integrating industrial chain knowledge subgraphs,and visualizing industrial chain knowledge graphs.Fully leverage the advantages of crowdsourcing participants and allocate subgraph construction tasks to numerous crowdsourcing participants.Secondly,a subgraph fusion strategy based on the similarity of industrial chain links is proposed.This strategy removes redundancy and expresses imprecise industrial chain links through preprocessing,and achieves the fusion of industrial chain knowledge subgraphs based on the calculation of link similarity and link weight.Finally,the fused industry chain knowledge graph will be stored in the Neo4 j database for visual display.(2)For the service mapping problem,this paper proposes a similarity algorithm based on weighted word2 vec.Because the industry chain data and service data are highly professional,the similarity calculation is realized by combining TF-IDF on the basis of semantic similarity.This algorithm can fully consider the Semantic information and professionalism of industry chain data and service data,so as to bind the services that meet the established rules with the industry chain links.(3)Based on the relevant technical methods mentioned above,this article designs and implements a service organization management system based on the industry chain knowledge graph.The system can provide validation for the release and execution of crowdsourcing tasks,the construction of industry chain knowledge graphs,service mapping,and other functions.