Design And Implementation Of Vehicle-cargo Matching Recommendation System Based On Big Data Technology

In recent years,under the influence of the powerful force of "Internet + logistics",the demand for road transportation has become larger and larger,and the accompanying problems have become more and more prominent.The road freight market not only has low concentration and low transaction efficiency,but also has a large and disordered number of small logistics companies.There are more than 30 million freight drivers,who are responsible for more than 70% of the total freight volume.Therefore,the problem of information asymmetry and distortion is very serious,which also causes the general situation that it is difficult for the cargo to find the carrier and the carrier to find the goods.This transaction mode is very unfavorable for the long-term development of the freight market.According to relevant statistics,since the rapid emergence of vehicle-cargo-matching freight platforms in 2014,the number of freight platform apps has reached hundreds.In addition to mobile apps,there are many websites and We Chat public accounts that push vehicle and source information.It provides convenience for cargo owners to reduce the problem of information asymmetry,which has become a new trend in the logistics industry.However,as we all know,when the economy develops to a certain level,the market will inevitably pursue the quality and efficiency of economic development,and the road freight industry is no exception.The efficiency level of road freight directly affects the quality of the development of the entire freight industry.Management and evaluation are particularly important.However,the existing reputation evaluation mechanism has problems such as single evaluation index,simple evaluation model,and poor differentiation ability,which cannot fully reflect the real reputation status of vehicle and cargo matching participants.Based on the above problems,in the big data environment,this paper extensively collects the evaluation indicators of both sides of the vehicle and cargo matching,from the four dimensions of user basic information,service quality,complaints and contract performance and trustworthiness,to establish a reliable multi-dimensional vehicle and cargo matching participants.The reputation evaluation model,and the fuzzy analytic hierarchy process combined with the triangular fuzzy theory and the analytic hierarchy process to reduce the subjective judgment in the multi-dimensional reputation evaluation process,let the data "speak",and ensure the quality of the transaction.This paper studies the key factors affecting the quality and efficiency of vehicle and cargo matching,and proposes a vehicle and cargo matching model based on big data technology.The entire matching model is divided into three stages.The first stage is state information matching.Using the current state information of vehicles and goods published in the freight platform,the vehicle set and the source set are preliminarily screened to obtain valid and matching vehicles and source sets.The second stage is service information matching,which integrates the results screened in the first stage to obtain the currently valid and matchable attribute information of vehicles and goods.Based on this information,preliminary matching of vehicles and goods is carried out.The third stage is comprehensive information matching,obtaining a list of matching results obtained in the previous stage,according to the respective needs of the driver and the owner,comprehensively considering the matching degree of vehicle and cargo and the urgency of the source of goods.The top k results from large to small are recommended to shippers and drivers respectively.This paper uses the actual data of a highway logistics platform and conducts case analysis to further test the reliability of the model.The test results show that the multi-dimensional reputation evaluation model is more comprehensive and accurate than the existing reputation evaluation model,and has great practical value..The vehicle and cargo matching model based on big data technology can effectively improve the quality and efficiency of vehicle and cargo matching,effectively reduce the transaction risk in the process of vehicle and cargo matching,and has strong practicability.