The invention relates to an Internet-of-vehicles 
big data cross-
domain analysis fusion method, which is mainly characterized in that an Internet-of-vehicles 
cloud data mining architecture is established, and 
the Internet-of-vehicles 
cloud data mining architecture comprises a distributed 
data access engine, a parallel mining engine, proxy nodes and a 
Web server cluster; performing 
data mining by adopting an Internet-of-vehicles 
data mining algorithm; and realizing a parallel function of the 
shared memory by adopting a 
shared memory parallel computing technology. According to the method, a clouddata mining architecture which is composed of a distributed 
data access engine, a parallel mining engine, a 
Web server cluster and agent nodes and can support 
parallel computing is adopted, so that the supporting capability for 
mass data is improved; through a data preprocessing technology, an 
uncertain data preprocessing technology and an Internet-of-vehicles industry 
data processing and fusiontechnology, support of Internet-of-vehicles specific data such as 
streaming data is optimized; based on novel 
data mining algorithms such as mining, analysis, clustering technology, 
behavior recognition and 
anomaly detection of 
the Internet-of-vehicles 
streaming data, the intelligent level of the 
system is improved.