Online vehicle recommending and sequencing method on basis of preference learning of owners of goods

The invention provides an online vehicle recommending and sequencing method on the basis of preference learning of owners of goods. The online vehicle recommending and sequencing method comprises the following steps: firstly establishing a full-connection diagram according to related attribute information of all vehicles; then calculating a probability matrix and an expected matrix of browsed vehicles according to the vehicles which are browsed by the owners of goods and attract the interest of the owners of goods; calculating a matching-degree vector of the vehicles not browsed by the owners of goods and the expected vehicles of the owners of goods, wherein each component of the matching-degree vector represents the matching degree of the corresponding vehicles and the expected vehicles of the owners of goods; and finally, sequencing the vehicles not browsed by the owners of goods according to the matching degree, and repeating the process till the owners of goods select the expected vehicles. The online vehicle recommending and sequencing method provided by the invention has the advantages that the vehicles selected subsequently by users are updated and sequenced by online learning to the preference information of the users, so that the matching degree between the vehicle sequencing result and the user expect is increased, the user experience is improved and the vehicle searching efficiency is improved.