Research On The User Credit And Message Push Algorithm On Crowdsourcing Plaform

Crowdsourcing is a kind of thinking model which is relying on the internet to together with the masses, solve the problem and complete the task.This paper will take crowdsourcing mode applied to colleges and universities,constructed a shared logistics mode of crowdsourcing platform.This platform will piggybacking items, emergency rescue and other services.such not only provide more opportunities for part-time students,but also save time for those needed,while they are able to take advantage of idle resources, transfer the fragments of time into value.Crowdsourcing system often take pull mode at current,the user must to find and get the task initiatively.this can not insure the task to be executed by the right worker in timely,and result in the completion of the task will be not in high quality.Secondly, the open characteristics of the crowdsourcing model will bring some potential safety risks, for instance, the information asymmetry between the traders, for the honesty of the mession worker,the authenticity of the goods, the lost or damaged to the commodities. For this problem,this paper will give the corresponding treatment plan.First of all, this paper adopts push mode, and initiatively to push the task to the right workers.this paper adopts a new adaptive message push strategy, which is based on the analysis of the operation parameters of the mobile terminal and used for the dynamic distribution of the terminal,ensure the real-time performance of the message.Such strategy can take into account the diversity of the terminal, electricity consumption, traffic consumption. In addition, a new adaptive message push strategy is optimized, which can increase the diversity of the terminal, and guarantee the real-time push of the message.Secondly,facing the security problem of the platform, this paper establishes a credit evaluation model, which is suitable for detect and estimate the campus platform. The credit evaluation model algorithm comprehensively considers the advantages and disadvantages of the existing credit model of electronic commerce, like introducing the service weighted scoring, transaction amount, punishment factor, the evaluation of people’s credit. Finally, with the simulation of the new algorithm credit model using octave as simulation tool,After analysis and conclusions: the new credit evaluation model of crowdsourcing perfectly prevents credit fraud or malicious behavior.