Computer Science ›› 2019, Vol. 46 ›› Issue (2): 42-49.doi: 10.11896/j.issn.1002-137X.2019.02.007

• Big Data & Data Science • Previous Articles     Next Articles

Multilevel and Intelligent Rent-seeking and Matching Resource Strategy and Value Creation of Public Service Platform in Big Data Environment

BI Ya, YUAN Hui-qun, CHU Ye-ping, LIU hui   

  1. College of Business Management,Hubei University of Economics,Wuhan 430205,China
  • Received:2018-08-31 Online:2019-02-25 Published:2019-02-25

Abstract: The problem of resource rent-seeking and matching based on public service platform in big data environment was studied in this paper.In view of the unstructured features of large data,the semantic distance was redefined by considering the path distance,connection depth and breadth of the ontology tree,and a formal five element description mo-del based on semantic distance was proposed to eliminate the complexity of the large data in the underlying structure and type.In view of the large scale of large data,a strategy of resource classification intelligent rent-seeking and matching was proposed.First,a coarse particle filter is carried out to reduce the range of resource matching and speed up the matching speed of the algorithm by means of coarse particle size of Scategory and Sstatus which has few and simple parameters.Then by fine-grained matching of Sability and SQoS,a resource ordering aggregate satisfying the requirement of the demand side is finally obtained.Experiments show that the computational efficiency of this method is significantlyhigherthan that of traditional multi-threading algorithm,and the precision and recall of this method are also better than those of common resource rent-seeking and matching algorithms.Compared with the existing resource matching algorithm,this method is effective and feasible.It can not only realize the rapid rent-seeking and accurate search of the resources on the public service platform,but also further enhance the value creation of resources under the large data environment.

Key words: Big data, Public service platform, Rent-seeking and matching, Semantic distance, Value creation

CLC Number: 

  • TP274
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