1. A method for searching information, comprising: receiving current query data from a client; extracting generic attribute features of the current query data, wherein the generic attribute features are used for calculating a plurality of confidence degrees of the current query data that correspond to a plurality of categories, each of the confidence degrees indicating a degree of confidence that the current query data belongs to a respective one of the plurality of categories; determining the plurality of confidence degrees of the current query data based at least in part on the generic attribute features, wherein the determining of the plurality of confidence degrees is based on a maximum entropy model, a linear regression, or a support vector machine model; selecting a category based at least in part on the plurality of confidence degrees, the selected category being one of the plurality of categories and having a confidence degree higher than a confidence degree of another category; searching in the selected category for a search result that corresponds to the current query data; and returning the search result.
2. The method of claim 1 , wherein the generic attribute features comprise a word-level feature that corresponds to a keyword in the current query data.