Preference Research On Carrier's Behavior Of Picking Orders Of NTOCC Platform Based On Data Mining

With the rise of the "Internet+Logistics" platform,a new format has emerged in the transportation sector-NTOCC(Non-Truck Operating Common Carrier).This new format makes transactions safer and more efficient,and provides more protection to the cargo owners and carriers.In the process of trading in the NTOCC platform,the database will store a large amount of data,including information about the owners and transaction data.Using efficient data analysis and data mining can help companies discover more rules behind big data.Similarly,the application of data mining technology in the field of the NTOCC can help platform enterprises to realize the transformation from big data to commercial information,and provide strong support for business operations.This paper will study the preference of carrier's behavior of picking orders of NTOCC platform.Firstly,relevant literature review is carried out for the research subjects;relevant research on consumer behavior theory level will be introduced,and the related research of data mining technology in the field of consumer behavior is further elaborated,and the research status of data mining and the specific use process of related model algorithms will be summarized..Secondly,this paper will analyze the characteristics and value of the carrier of the NTOCC platform.According to the user value theory and consumer behavior theory,we will construct the user value system of the carrier of the NTOCC platform,and based on the system,the clustering mining technology(K-means algorithm)is used to subdivide the carrier users,according to the subdivision results.Different user groups perform feature analysis to provide relevant marketing strategies for the NTOCC platform.Finally,this paper analyzes the behavior preference of the carrier's users based on association mining.Based on the results of cluster mining,the association rules are used to mine the preferences of the group.The multi-dimensional multi-layer association rule model will be constructed,and the association mining technology(Apriori algorithm)is used to find the preference behavior of the different carrier user groups,and the corresponding recommendation scheme is proposed in a targeted manner.This paper presents conclusions and future research directions in the last chapter.These conclusions show that the research results of this paper are scientific.According to the recent data verification of Z platform,such preference conclusions exist in actual operation.The index system and related models designed in this paper are of great significance to the relevant work of the Z platform,and can be extended to more related work of the NTOCC platform.