Abstract:
A method for matching cross-area products includes steps as follows. First and second local product lists are matched through text similarity and graph similarity, and a corresponding relation of the matched first and second products is built. A first difference of topic probability vector of the first and second products and a second difference of topic probability vector of third and fourth products are calculated. If the first difference of topic probability vector is similar to the second difference of topic probability vector, the third and fourth products that are failed to be matched are built a corresponding relation. A cross-area product list of the first and second local product lists is generated. First and second local electronic commerce product lists are added in the first and second local area lists. The first and second local area lists corresponding to the cross-area product list are displayed on a displaying device.
Abstract:
An electronic calculating apparatus, a method and a non-transitory machine-readable medium are provided. The electronic calculating apparatus includes an input/output (I/O) interface, a knowledge tree database and a processor. The I/O interface receives first data of a user, wherein the first data is comprised of a natural language character string. The knowledge tree database stores a context knowledge tree. The processor receives the first data of the user via the I/O interface, analyzes the first data and generates context characteristic information, and substitutes the context characteristic information into the context knowledge tree to generate first context recommend information. The processor then enables a display apparatus to display the first context recommend information.