10. A query system based on a vertical search, comprising: a query server that: receives a user query; obtains a first category model from a category model warehouse based on the user query to generate a first query result, the first category model comprising one or more commodity categories that correspond to one or more keywords in the user query; obtains one or more commodity categories corresponding to the user query from a commodity warehouse to generate a second query result; and generates a final query result by combining the first query result and the second query result, wherein generating the final query result comprises: obtaining a first combined result comprising commodity categories that are in both the first query result and the second query result, the first combined result further comprising weights corresponding to the commodity categories in the first combined result and being a combination of weights from the first query result and from the second query result; obtaining a second combined result comprising commodity categories and corresponding weights in the second query result; increasing the weights in the first combined result to render the weights corresponding to the commodity categories in the first combined result to be respectively higher than the weights corresponding to the commodity categories in the second combined result; and arranging the commodity categories in the first combined result according to the weights in the first combined result in a descending order to provide the first combined result to a user; a log server that generates a log based on the user query and user's clicking operations in response to the final query result; and a modeling server that generates a second category model from statistical analysis of data in the log.
10. A query system based on a vertical search, comprising: a query server that: receives a user query; obtains a first category model from a category model warehouse based on the user query to generate a first query result, the first category model comprising one or more commodity categories that correspond to one or more keywords in the user query; obtains one or more commodity categories corresponding to the user query from a commodity warehouse to generate a second query result; and generates a final query result by combining the first query result and the second query result, wherein generating the final query result comprises: obtaining a first combined result comprising commodity categories that are in both the first query result and the second query result, the first combined result further comprising weights corresponding to the commodity categories in the first combined result and being a combination of weights from the first query result and from the second query result; obtaining a second combined result comprising commodity categories and corresponding weights in the second query result; increasing the weights in the first combined result to render the weights corresponding to the commodity categories in the first combined result to be respectively higher than the weights corresponding to the commodity categories in the second combined result; and arranging the commodity categories in the first combined result according to the weights in the first combined result in a descending order to provide the first combined result to a user; a log server that generates a log based on the user query and user's clicking operations in response to the final query result; and a modeling server that generates a second category model from statistical analysis of data in the log. 14. A query system as recited in claim 10 , wherein the modeling server further: obtains a statistical analysis result based on statistical analysis of the user query and corresponding clicking information in the log, the statistical analysis result comprising a plurality of commodity categories, associated attribute categories, and weights corresponding to the plurality of commodity categories and the associated attribute categories that correspond to the user query, the weights corresponding to the plurality of commodity categories and the associated attribute categories comprising number of clicks on the plurality of commodity categories and the associated attribute categories, clicking probability related to the plurality of commodity categories and the associated attribute categories, or both; and arranges the statistical analysis result as a category tree to generate the second category model.