A computer implemented system comprising the following computer executable components: a classification encoder component that summarizes a query log into a classification based on demographics, wherein the classification is in the form of a tree structure to summarize the query log, wherein the classification encoder component leverages information stored in the query log by mining a plurality of queries from the query log and distributing the plurality of queries among nodes to form the tree structure; a local language models encoder component that expands the tree structure to form localized language models, to facilitate a search for local interests, wherein in said localized language models, probabilities of queries depend on demographics, wherein the tree structure comprises a localized language model at each node in the tree structure; a localized language model component that blends generic answers with local answers, wherein said localized language model component uses a plurality of localized language models associated with nodes on a path from a leaf in the tree structure to a root of the tree structure, wherein a leaf of the tree structure corresponds to a specific demographic location and the root of the tree structure corresponds to a generic demographic location shared by all leafs in the tree structure, and wherein any node in the tree structure represents queries issued from a region, and wherein the further down in the tree structure a node appears, the more specific a region it covers; and an artificial intelligence component that facilitates smoothing of the classification, wherein said smoothing comprises moving one or more of said plurality of queries among levels of the tree structure such that general queries move towards the root of the tree structure and queries of local interest reside at lower levels of the tree structure. a classification encoder component that summarizes a query log into a classification based on demographics, wherein the classification is in the form of a tree structure to summarize the query log, wherein the classification encoder component leverages information stored in the query log by mining a plurality of queries from the query log and distributing the plurality of queries among nodes to form the tree structure; a local language models encoder component that expands the tree structure to form localized language models, to facilitate a search for local interests, wherein in said localized language models, probabilities of queries depend on demographics, wherein the tree structure comprises a localized language model at each node in the tree structure; a localized language model component that blends generic answers with local answers, wherein said localized language model component uses a plurality of localized language models associated with nodes on a path from a leaf in the tree structure to a root of the tree structure, wherein a leaf of the tree structure corresponds to a specific demographic location and the root of the tree structure corresponds to a generic demographic location shared by all leafs in the tree structure, and wherein any node in the tree structure represents queries issued from a region, and wherein the further down in the tree structure a node appears, the more specific a region it covers; and an artificial intelligence component that facilitates smoothing of the classification, wherein said smoothing comprises moving one or more of said plurality of queries among levels of the tree structure such that general queries move towards the root of the tree structure and queries of local interest reside at lower levels of the tree structure.